Gender-specific markers for diagnosing prognosis and determining treatment strategy for renal cancer patients

ABSTRACT

The present invention relates to markers for diagnosing the difference in effects of renal cancer treatment or the prognosis of renal cancer patients, according to the gender of renal cancer patients. The survival rate and recurrence rate of renal cancer of a particular gender respectively relate to the mutation of genes, of the present invention, in renal cancer patients, and thus the mutated genes of the present invention can be used as markers in predicting, on the basis of gender, the difference in effects of renal cancer treatment or the prognosis of renal cancer patients.

TECHNICAL FIELD

The present invention relates to a marker for diagnosing prognosis of a patient with kidney cancer, a kit for diagnosing prognosis of a patient with kidney cancer including the same, and a method of providing information required to diagnose the prognosis of kidney cancer and determine a therapeutic strategy for kidney cancer using the kit for diagnosing prognosis of a patient with kidney cancer.

BACKGROUND ART

The kidney is an important urinary organ that serves to excrete waste materials from the body by filtering blood to generate urine. Also, the kidney is an important endocrine organ that produces hormones such as angiotensin that controls the blood pressure, erythropoietin as a haemopoietic factor, and the like.

Tumors occurring in the kidney include renal cell carcinoma arising from the adults, Wilms' tumor arising from the children, sarcoma as a rare tumor, and the like. Later on, the renal cell carcinoma as a malignant tumor having the highest incidence rate is referred to as kidney cancer. In Japan, the kidney cancer develops at an incidence frequency of approximately 2.5 per every 100,000 persons. In this case, the kidney cancer tends to occur at a higher frequency for men, that is, the proportion of men and women is 2 to 3:1. Among the urological malignant tumors, the kidney cancer is the most common tumor following prostate cancer and bladder cancer. The kidney cancer refers to renal cell carcinoma that develops mostly in the parenchyma (including medulla and cortex in which cells producing urine in the kidney are held together) of the kidney.

A genetic factor is known to be one of risk factors for kidney cancer, but such risk factors generally include smoking, excessive fat intake, and the like. Also, it has been know that the incidence rate of tumor is high in patients receiving dialysis for a long time.

In the case of kidney cancer, patients rarely have any observable symptoms when a tumor has the maximum diameter of 5 cm or less. Generally, the kidney cancer is often found when patients take a medical examination through a CT scan, and the like. Hematuria, celioncus, pain, and the like appear as the symptoms of large tumors. Also, pyrexy, weight loss, anaemia, and the like are often caused as the systemic symptoms, and erythrocytosis, hypertension, hypercalcemia, and the like are rarely caused by endocrine factors. Meanwhile, development of phlebismus or varicocele in the abdominal wall often occurs by tremors in the inferior vena cava of the kidney. Approximately 20% of the kidney cancers are found from the metastasis to the lungs or bone. Because tumor has a strong tendency to spread into the vein in the case of kidney cancer, the kidney cancer easily metastasizes into other organs.

Kidney cancer has few symptoms when it has a small tumor size, but has symptoms only when the tumor grows to push organs. Therefore, because the diagnosis of the kidney cancer is often delayed, the metastasis of kidney cancer into other organs is found in approximately 30% of patients, compared to when the kidney cancer is diagnosed at an early stage. The most common symptom is hematuria, but is found only in 60% of the patients. On the contrary, because patients have symptoms such as dyspnoea, cough, headaches, and the like depending on the metastasized sites, the patients who are diagnosed with kidney cancer due to such metastatic symptoms also account for 30% of the entire patients. Because hypertension, hypercalcemia, hepatic dysfunction, and the like may be caused by certain hormones especially produced by cancer cells, tumors may be often found while checking these other symptoms in kidney cancer. However, there are many current cases in which tumors are found by chance in imaging tests while patients receive medical checkups without any symptoms. In this case, because the tumors are generally found at early stages, the results of tumor treatment have been relatively successful. Therefore, it has been known that it is very important to diagnose such kidney cancer.

In U.S., patients with kidney cancer account for approximately 3% of adult cancer patients, and approximately 32,000 cancer patients are newly reported every year. Also, approximately 12,000 cases are assumed to die from kidney cancer, with an increasing incidence frequency worldwide every year. In Korea, the incidence frequency of kidney cancer is reported to be lower than that in U.S. Therefore, the National Cancer Registry data (2012) reported that 1,578 new cases of cancer patients are registered so that it accounts for 1.6% of the total number of cancer occurrences. Kidney cancer occurs commonly in people between 40 to 60 years old, and the current state of cancer incidence by gender (National Cancer Registry data on 2012) reports that kidney cancer occurs most commonly in people in their 60s (479 cases, 30.2%), followed by 50s (412 cases, 26.0%), and 40s (268 cases, 16.9%) in the corresponding order thereof When patients with kidney cancer undergo surgery to remove the tumor after the onset of kidney cancer, the patients have a high survival rate. However, because the patients have no clear symptoms at an early stage, it is difficult to diagnose kidney cancer at this stage. For these reasons, there is a need for development of a marker capable of diagnosing kidney cancer at an early stage and checking the patients' remaining lives after the onset of cancer.

Transglutaminase 2 (Registered Korean Patent No. 1267580) is disclosed as a marker used to detect or diagnose kidney cancer in humans. Although markers for diagnosing cancers including kidney cancer have been developed, there is no research on markers capable of determining the prognosis of patients with kidney cancer, particularly the relationship between the gender of patients with kidney cancer and the mutation of a certain gene.

To develop a therapeutic agent for diagnosing kidney cancer or healing patients with kidney cancer so as to determine a therapeutic strategy, the present inventors have conducted research on the relationship between the gene mutation and the gender of the patients found in the patients with kidney cancer on the basis of the need for development of the markers capable of diagnosing the prognosis of the patients with kidney cancer.

DISCLOSURE Technical Problem

To apply a suitable therapeutic strategy to patients with kidney cancer, a development of markers which aid in predicting the prognosis of patients with kidney cancer and determining a therapeutic strategy thereof is needed. Therefore, it is an object of the present invention to provide a marker which aids in predicting the prognosis of patients with kidney cancer and determining a therapeutic strategy thereof based on the gender of the patients with kidney cancer.

Technical Solution

To solve the above problems, according to an aspect of the present invention, there is provided a kit for providing information required to predict a therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit is able to detect a gender-specific marker that is a mutation of a gene coding for at least one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1.

According to another aspect of the present invention, there is provided a method of providing information required to verify a difference in therapeutic effect against kidney cancer according to the gender of patients with kidney cancer. In this case, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer whose gender is identified; amplifying the DNA test sample using the kit; determining whether or not there is a gender-specific marker specific to a gender group of target patients from the results of amplification; treating the patient with kidney cancer, in which the gender-specific marker is identified, with any candidate material for treating kidney cancer or healing the patient with kidney cancer using any method; and choosing any candidate material for treating kidney cancer or any method of treating kidney cancer as a therapeutic candidate material or a therapeutic method, which is suitable for the gender group of patients with kidney cancer in which the gender-specific marker is identified, when the any candidate material or the any method is used to treat kidney cancer.

According to still another aspect of the present invention, there is provided a method of providing information required to diagnose prognosis of kidney cancer according to the gender of a patient with kidney cancer. In this case, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer; amplifying the DNA test sample using the kit; and determining whether or not there is a gender-specific marker from the results of amplification.

Advantageous Effects

Because there is a relationship between the gender of a patient with kidney cancer and a mutation of a gene selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1, all genes of which are found in the present invention, the presence of the mutation of the gene can be checked to predict a difference in therapeutic effect against kidney cancer and a difference in survival rate of the patient with kidney cancer according to the gender of the patient with kidney cancer.

In addition, because there is a relationship between a survival rate of the patient with kidney cancer who has a certain gender and a mutation of one gene selected from a gene group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1, all genes of which are found in the present invention, or a relationship between the mutation of the gene and a relapse rate of kidney cancer, mutations of the genes according to the present invention can be used as the marker to predict the prognosis of the patient with kidney cancer.

However, the effects of the present invention are not limited to the effects as described above, and other effects not disclosed herein will be clearly understood from the following detailed description by those skilled in the art.

DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram showing gender-specific mutant genes specifically shown from candidate genes when patients with kidney cancer who are classified according to the gender thereof are compared with each other. Each of numerical values represents the number of the patients with kidney cancer in which mutated genes are identified.

FIGS. 2 to 10 are graphs plotted for an overall survival rate or a disease-free survival rate of patients with kidney cancer (red) who have mutations in respective ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes and patients with kidney cancer (blue) who have no mutations in the corresponding genes.

BEST MODE

Unless defined otherwise in this specification, all the technical and scientific terms used herein have the same meanings as what are generally understood by a person skilled in the related art to which the present invention belongs. In general, the nomenclatures used in this specification and the experimental methods described below are widely known and generally used in the related art.

Hereinafter, the present invention will be described in detail.

1. Gender-Specific Mutant Genes in Patient with Kidney Cancer and Primer Sets Capable of Detecting the Mutant Genes

One aspect of the present invention provides a kit for providing information required to predict a difference in therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit may detect a gender-specific marker that is a mutation of at least one gene selected from a gene group consisting of ACSS3 (Gene Bank Accession Number: NM_024560.3), ADAM21 (Gene Bank Accession Number: NM_003813.3), AFF2 (Gene Bank Accession Number: NM_002025.3), ALG13 (Gene Bank Accession Number: NM_001099922.2), ARSF (Gene Bank Accession Number: NM_001201538.1), BAP1 (Gene Bank Accession Number: NM_004656.3), BRWD3 (Gene Bank Accession Number: NM_153252.4), CFP (Gene Bank Accession Number: NM_001145252.1), COL4A5 (Gene Bank Accession Number: NM_000495.4), CPEB1 (Gene Bank Accession Number: NM_030594.4), ERBB2 (Gene Bank Accession Number: NM_004448.3), FAM47A (Gene Bank Accession Number: NM_203408.3), HSP90AA1 (Gene Bank Accession Number: NM_001017963.2), IRAK1 (Gene Bank Accession Number: NM_001569.3), KDMSC (Gene Bank Accession Number: NM_004187.3), KDM6A (Gene Bank Accession Number: NM_021140.3), LRP12 (Gene Bank Accession Number: NM_013437.4), NCOA6 (Gene Bank Accession Number: NM_001242539.2), NHS (Gene Bank Accession Number: NM_198270.3), PHF16(JADE3) (Gene Bank Accession Number: NM_001077445.2), RGAG1 (Gene Bank Accession Number: NM_020769.2), SCAF1 (Gene Bank Accession Number: NM_021228.2), SCRN1 (Gene Bank Accession Number: NM_001145514.1), SH3TC1 (Gene Bank Accession Number: NM_018986.4), TBC1D8B (Gene Bank Accession Number: NM_017752.2), TET2 (Gene Bank Accession Number: NM_001127208.2), TEX13A (Gene Bank Accession Number: NM_001291277.1), ULK3 (Gene Bank Accession Number: NM_001099436.3), WNK3 (Gene Bank Accession Number: NM_001002838.3), and ZNF449 (Gene Bank Accession Number: NM_152695.5).

The full names of abbreviations for the genes may be ACSS3 (Homo sapiens acyl-CoA synthetase short chain family member 3), ADAM21 (Homo sapiens ADAM metallopeptidase domain 21), AFF2 (Homo sapiens AF4/FMR2 family member 2), ALG13 (UDP-N-acetylglucosaminyltransferase subunit), BAP1 (BRCA1-associated protein 1), BRWD3 (bromodomain and WD repeat domain containing 3), COL4A5 (collagen type IV alpha 5 chain), CPEB1 (cytoplasmic polyadenylation element binding protein 1), ERBB2 (erb-b2 receptor tyrosine kinase 2), HSP90AA1 (heat shock protein 90 alpha family class A member 1), IRAK1 (interleukin 1 receptor associated kinase 1), KDMSC (lysine demethylase 5C), KDM6A (lysine demethylase 6A), LRP12 (LDL receptor related protein 12), NCOA6 (nuclear receptor coactivator 6), NHS (NHS actin remodeling regulator), RGAG1 (retrotransposon Gag like 9), SCAF1 (SR-related CTD associated factor 1), SH3TC1 (SH3 domain and tetratricopeptide repeats 1), TBC1D8B (TBC1 domain family member 8B), TET2 (tet methylcytosine dioxygenase 2), TEX13A (testis-expressed 13A), ULK3 (unc-51 like kinase 3), WNK3 (WNK lysine-deficient protein kinase 3), ARSF (arylsulfatase F), CFP (complement factor properdin), FAM47A (family with sequence similarity 47 member A), PHF16 (jade family PHD finger 3), ZNF449 (zinc finger protein 449), and SCRN1 (secernin 1).

According to one exemplary embodiment of the present invention, there is provided a kit for providing information required to predict a difference in therapeutic effect against kidney cancer or diagnose prognosis of a patient with kidney cancer according to the gender of the patient with kidney cancer, wherein the kit may detect a mutation of at least one gene selected from the following genes: a mutation of a gene coding for at least one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1.

In the present invention, the term ‘diagnosis’ refers to a process in which the presence or nature of a pathologic status is determined, that is, a process in which a difference in therapeutic effect against cancer according to the gender of a cancer patient is verified for the objects of the present invention and a process in which the relapse and metastasis of cancer, drug response and resistance, and the like in the corresponding subject after cancer treatment are judged. Preferably, when the mutations of the genes of the present invention are used, it is also possible to predict a difference in survival rate by checking whether there are mutations in a test sample of a patient with kidney cancer. In this case, a difference in therapeutic effect against kidney cancer and the prognosis of the corresponding patient in the future according to the gender of the corresponding patient with kidney cancer may be determined from the difference in survival rate.

In the present invention, the term ‘prognosis’ refers to the prediction of the progress and cure of a disease having a probability of cancer-attributable death or progression, including, for example, the relapse and metastatic spread of a neoplastic disease such as cancer, and drug resistance. The prognosis may refer to a prediction of the prognosis of kidney cancer for the objects of the present invention. Preferably, the prognosis may refer to a prediction of a disease-free survival rate or survival rate of the patient with kidney cancer.

In the present invention, the term ‘cancer’ includes any members belonging to a class of diseases characterized by the uncontrolled growth of abnormal cells. The term includes all stages and grades of cancers, including all types of known cancers and neoplastic conditions, cancers before/after metastasis, regardless whether the cancer is characterized by any one malignant, benign, soft tissue, or solid cancer.

In the present invention, the term ‘gene’ and modified products thereof include DNA fragments associated with the synthesis of polypeptide chains; each of the DNA fragments includes regions upstream and downstream from a coding region, for example, a promoter and a 3′-untranslated region, respectively, and also includes intervening sequences (introns) between respective coding fragments (exons).

The mutation of the gene may include any one or more mutations, and may, for example, have at least one mutation selected from the group consisting of truncating mutation, missense mutation, nonsense mutation, frameshift mutation, in-frame mutation, splice mutation, and splice_region mutation. The frameshift mutation may be at least one selected from a frameshift insertion (FS ins) mutation and a frameshift deletion (FS del) mutation. The in-frame mutation may be at least one selected from an in-frame insertion (IF ins) mutation and an in-frame deletion (IF del) mutation.

In conjunction with mutations in a polypeptide sequence, the term “X#Y” is obviously recognized in the related art. Here, the sign “#” represents a mutation position with respect to the amino acid number of a polypeptide, “X” represents an amino acid found at the position of a wild-type amino acid sequence, and “Y” represents a mutant amino acid found at the same position. For example, the sign “G1717V” with respect to a BAZ2B polypeptide means that there is a glycine residue at amino acid number 1,717 of a wild-type BAZ2B sequence, and the glycine residue is replaced with valine in a mutant BAZ2B sequence.

The mutations of the genes are as follows:

The mutation of the gene coding for ACSS3 is a nonsense mutation ‘R634*’, a splice mutation A152_splice' (where T is substituted with C at position 81503485 on the chromosome), or a missense mutation ‘G268D’, wherein the sign in a notation of the nonsense mutation means that the synthesis of amino acids is terminated at the corresponding amino acid position (a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 1; the mutation of the gene coding for ADAM21 is at least one mutation selected from the group consisting of N265Y, R408C, T589S, and I161V in an amino acid sequence set forth in SEQ ID NO: 2; the mutation of the gene coding for AFF2 is at least one missense mutation selected from the group consisting of S770F, P513H, T640N, and 1149K in an amino acid sequence set forth in SEQ ID NO: 3; the mutation of the gene coding for ALG13 is at least one missense mutation selected from P925T and V456E, or a frameshift deletion (FS del) mutation ‘L195Pfs*23’, where a notation of the frameshift mutation is based on the amino acid type (an amino acid position) and the amino acid type fs* (the number of nucleotides downstream from the amino acid position to a stop codon) (both the FS ins mutation and FS del mutation are denoted by the same notation, and a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 4; the mutation of the gene coding for BAP1 is a nonstart mutation ‘M1?’ (where T is substituted with C at position 52443894 and C is substituted with T at position 52443892 on the chromosome), at least one nonsense mutation selected from the group consisting of G128*, E402*, Q253*, Q267*, S460*, Y627*, S279*, R60*, Q40*, Q156*, and K626*, at least one FS del mutation selected from the group consisting of E283Gfs*52, V335Efs*56, K711Sfs*25, R700Gfs*36, D74Efs*4, and D407Vfs*23, at least one missense mutation selected from the group consisting of F170V, F170C, E31A, N78S, L49V, D75G, SlOT, N229H, G109V, L17P, A145G, and A1061T, at least one splice mutation selected from the group consisting of X23_splice (where C is substituted with T at position 52443729 on the chromosome), X41_splice (where A is substituted with G at position 52443568 on the chromosome), X41_splice (where A is substituted with T at position 52443568 on the chromosome), X23_splice (where ACCTGCGATGAGGAAAGGAAAGCAG at positions 52443623 to 52443647 are deleted from the chromosome), and X311_splice (where C is substituted with A at position 52439311 on the chromosome), or an in-frame deletion (IF del) mutation ‘K659del’, where the sign ‘del’ in a notation of the IF del mutation represents a deletion of the corresponding amino acid at the corresponding amino acid position (a description thereof is omitted hereinafter), in an amino acid sequence set forth in SEQ ID NO: 5; the mutation of the gene coding for BRWD3 is at least one missense mutation selected from G287A and I1747N in an amino acid sequence set forth in SEQ ID NO: 6; the mutation of the gene coding for COL4A5 is at least one missense mutation selected from the group consisting of P1184L, P756S, P1365S, G1427V, and A1656T, or a splice mutation ‘X1510_splice’ (where G is substituted with T at position 107935977 on the chromosome) in an amino acid sequence set forth in SEQ ID NO: 7; the mutation of the gene coding for CPEB1 is at least one missense mutation selected from S393R and G136V, or a splice mutation ‘X499_splice’ (where C is substituted with A at position 83215272 on the chromosome) in an amino acid sequence set forth in SEQ ID NO: 8; the mutation of the gene coding for ERBB2 is at least one missense mutation selected from the group consisting of E1114G, S649T, and V2191, or an FS ins mutation ‘N388Qfs*14’ in an amino acid sequence set forth in SEQ ID NO: 9; the mutation of the gene coding for HSP90AA1 is at least one missense mutation selected from the group consisting of D512N, H806R, I325T, and L167V in an amino acid sequence set forth in SEQ ID NO: 10; the mutation of the gene coding for IRAK1 is a nonsense mutation ‘Q280*’, or at least one missense mutation selected from V548M and Q584K in an amino acid sequence set forth in SEQ ID NO: 11; the mutation of the gene coding for KDMSC is at least one nonsense mutation selected from the group consisting of R681*, Q813*, E284*, E798*, Y639*, S1110*, K459*, and R215*, at least one missense mutation selected from the group consisting of E1152K, R1458W, G536W, C730R, E592V, C512W, C730F, and H733P, a splice mutation ‘X321_splice’ (where A is substituted with G at position 53244975 on the chromosome), or at least one FS del mutation selected from the group consisting of T471Vfs*5, Q1427Pfs*50, E122Vfs*14, E1131Sfs*16, H988Tfs*18, P27Lfs*46, F56Cfs*18, D1414Efs*54, and G845Rfs*2 in an amino acid sequence set forth in SEQ ID NO: 12; the mutation of the gene coding for KDM6A is a missense mutation ‘A30V’, an FS mutation ‘A1246Pfs*19’, or an IF del mutation ‘V156del’ in an amino acid sequence set forth in SEQ ID NO: 13; the mutation of the gene coding for LRP12 is at least one missense mutation selected from the group consisting of S622L, E639K, and V6711 in an amino acid sequence set forth in SEQ ID NO: 14; the mutation of the gene coding for NCOA6 is at least one missense mutation selected from the group consisting of G164E, N8771, N864Y, and V1444A, or an FS ins mutation ‘H832Sfs*47’ in an amino acid sequence set forth in SEQ ID NO: 15; the mutation of the gene coding for NHS is at least one missense mutation selected from the group consisting of C360R, P1107A, and D1069H in an amino acid sequence set forth in SEQ ID NO: 16; the mutation of the gene coding for RGAG1 is at least one missense mutation selected from the group consisting of A1015G, M858V, and G1053R in an amino acid sequence set forth in SEQ ID NO: 17; the mutation of the gene coding for SCAF1 is at least one FS ins mutation selected from the group consisting of A219Sfs*11, P211Tfs*19, P211Tfs*19, and A216Pfs*94, or an FS del mutation ‘A216Pfs*94’ in an amino acid sequence set forth in SEQ ID NO: 18; the mutation of the gene coding for SH3TC1 is at least one missense mutation selected from A375V and L180F or an FS del mutation ‘R2238Sfs*38’ in an amino acid sequence set forth in SEQ ID NO: 19; the mutation of the gene coding for TBC1D8B is at least one missense mutation selected from the group consisting of G1059V, A614T, and Y815F, or a nonsense mutation ‘S861*’ in an amino acid sequence set forth in SEQ ID NO: 20; the mutation of the gene coding for TET2 is at least one missense mutation selected from the group consisting of Q317K, L757V, V449E, N1714K, D194E, N1390H, R1451Q, M600I, and P554S, or a nonsense mutation ‘1(326*’ in an amino acid sequence set forth in SEQ ID NO: 21; the mutation of the gene coding for TEX13A is at least one missense mutation selected from R393S and Y257D, or a splice mutation ‘X199_splice’ (where C at position 104464282 is deleted from the chromosome) in an amino acid sequence set forth in SEQ ID NO: 22; the mutation of the gene coding for ULK3 is an FS del mutation ‘Q81Sfs*41’ and at least one missense mutation selected from D79H and L77V in an amino acid sequence set forth in SEQ ID NO: 23; the mutation of the gene coding for WNK3 is at least one nonsense mutation selected from S865* and Y589* and a missense mutation ‘E537G’ in an amino acid sequence set forth in SEQ ID NO: 24; the mutation of the gene coding for ARSF is a missense mutation ‘I42F’ in an amino acid sequence set forth in SEQ ID NO: 25; the mutation of the gene coding for CFP is at least one missense mutation selected from the group consisting of S27L, R359Q, and E135K, or an FS ins mutation ‘E323Gfs*34’ in an amino acid sequence set forth in SEQ ID NO: 26; the mutation of the gene coding for FAM47A is at least one missense mutation selected from R505H and E507Q, or at least one IF del mutation selected from L235_H246del and L235_H246del in an amino acid sequence set forth in SEQ ID NO: 27; the mutation of the gene coding for PHF16 is at least one missense mutation selected from K656Q and R207W in an amino acid sequence set forth in SEQ ID NO: 28; the mutation of the gene coding for ZNF449 is a missense mutation ‘F183I’ in an amino acid sequence set forth in SEQ ID NO: 29; and the mutation of the gene coding for SCRN1 is a missense mutation ‘D427Y’ or an FS ins mutation ‘A257Cfs*34’ in an amino acid sequence set forth in SEQ ID NO: 30.

An analytical method for diagnosing the prognosis of kidney cancer using the mutation of the gene, a next-generation sequencing (NGS) method, RT-PCR, a direct nucleic acid sequencing method, a microarray, and the like may be used. In this case, any methods may be used without limitation as long as the methods can be used to determine the presence of mutations using the mutation of the gene according to the present invention. According to one exemplary embodiment, the presence of mutations is determined using an anti-antibody (a mutant antibody against each gene) or nucleic acid probe that hybridizes with a mutant polynucleotide of each of the gene under a stringent condition. According to another exemplary embodiment, the anti-antibody or nucleic acid probe is detectably labeled. According to still another exemplary embodiment, a label is selected from the group consisting of an immunofluorescent label, a chemiluminescent label, a phosphorescent label, an enzyme label, a radioactive label, avidin/biotin, colloidal gold particles, coloring particles, and magnetic particles. According to yet another exemplary embodiment, the presence of mutations is determined using an radioimmunoassay, a Western blot assay, an immunofluorescence assay, an enzyme immunoassay, an immunoprecipitation assay, a chemiluminescence assay, an immunohistochemical assay, a dot-blot assay, a slot-blot assay, or a flow cytometric assay. According to yet another exemplary embodiment, the presence of mutations is determined by RT-PCR. According to yet another exemplary embodiment, the presence of mutations is determined by nucleic acid sequencing.

In the present invention, the term ‘polynucleotide’ generally refers to any polyribonucleotide or polydeoxyribonucleotide that may be unmodified RNA or DNA or modified RNA or DNA. Therefore, non-limiting examples of the polynucleotide as defined herein include single- and double-stranded DNAs, DNAs including single- and double-stranded regions, single- and double-stranded RNAs, and RNAs including single- and double-stranded regions, and hybrid molecules including DNAs and RNAs that may be single-stranded or more typically double-stranded or may include single- and double-stranded regions. Therefore, the DNA or RNA having a modified backbone due to its stability or other reasons is a ‘polynucleotide’ as described in the terms intended herein. Also, the DNA or RNA containing unusual bases such as inosine or modified bases such as a tritiated base is encompassed in the term ‘polynucleotide’ as defined herein. Generally, the term ‘polynucleotide’ includes all chemically, enzymatically and/or metabolically modified forms of an unmodified polynucleotide. The polynucleotide may be prepared by various methods including an in vitro recombinant DNA-mediated technology, and prepared by expression of DNA in cells and organisms.

Primer sets capable of detecting the mutation of the gene, that is, primer sets for diagnosing prognosis of kidney cancer are as follows: at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 31 and SEQ ID NO: 32, SEQ ID NO: 33 and SEQ ID NO: 34, and SEQ ID NO: 35 and SEQ ID NO: 36 to detect the mutation of ACSS3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 37 and SEQ ID NO: 38, SEQ ID NO: 39 and SEQ ID NO: 40, SEQ ID NO: 41 and SEQ ID NO: 42, and SEQ ID NO: 43 and SEQ ID NO: 44 to detect the mutation of ADAM21; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 45 and SEQ ID NO: 46, SEQ ID NO: 47 and SEQ ID NO: 48, SEQ ID NO: 49 and SEQ ID NO: 50, and SEQ ID NO: 51 and SEQ ID NO: 52 to detect the mutation of AFF2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 53 and SEQ ID NO: 54, SEQ ID NO: 55 and SEQ ID NO: 56, and SEQ ID NO: 57 and SEQ ID NO: 58 to detect the mutation of ALG13; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 59 and SEQ ID NO: 60, SEQ ID NO: 61 and SEQ ID NO: 62, SEQ ID NO: 63 and SEQ ID NO: 64, SEQ ID NO: 65 and SEQ ID NO: 66, SEQ ID NO: 67 and SEQ ID NO: 68, SEQ ID NO: 69 and SEQ ID NO: 70, SEQ ID NO: 71 and SEQ ID NO: 72, SEQ ID NO: 73 and SEQ ID NO: 74, SEQ ID NO: 75 and SEQ ID NO: 76, SEQ ID NO: 77 and SEQ ID NO: 78, SEQ ID NO: 79 and SEQ ID NO: 80, SEQ ID NO: 81 and SEQ ID NO: 82, SEQ ID NO: 83 and SEQ ID NO: 84, SEQ ID NO: 85 and SEQ ID NO: 86, SEQ ID NO: 87 and SEQ ID NO: 88, SEQ ID NO: 89 and SEQ ID NO: 90, SEQ ID NO: 91 and SEQ ID NO: 92, and SEQ ID NO: 93 and SEQ ID NO: 94 to detect the mutation of BAP1; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 95 and SEQ ID NO: 96, and SEQ ID NO: 97 and SEQ ID NO: 98 to detect the mutation of BRWD3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 99 and SEQ ID NO: 100, SEQ ID NO: 101 and SEQ ID NO: 102, SEQ ID NO: 103 and SEQ ID NO: 104, SEQ ID NO: 105 and SEQ ID NO: 106, SEQ ID NO: 107 and SEQ ID NO: 108, and SEQ ID NO: 109 and SEQ ID NO: 110 to detect the mutation of COL4A5; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 111 and SEQ ID NO: 112, SEQ ID NO: 113 and SEQ ID NO: 114, and SEQ ID NO: 115 and SEQ ID NO: 116 to detect the mutation of CPEB1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 117 and SEQ ID NO: 118, SEQ ID NO: 119 and SEQ ID NO: 120, and SEQ ID NO: 121 and SEQ ID NO: 122 to detect the mutation of ERBB2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 123 and SEQ ID NO: 124, SEQ ID NO: 125 and SEQ ID NO: 126, SEQ ID NO: 127 and SEQ ID NO: 128, and SEQ ID NO: 129 and SEQ ID NO: 130 to detect the mutation of HSP90AA1; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 131 and SEQ ID NO: 132, and SEQ ID NO: 133 and SEQ ID NO: 134 to detect the mutation of IRAK1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 135 and SEQ ID NO: 136, SEQ ID NO: 137 and SEQ ID NO: 138, SEQ ID NO: 139 and SEQ ID NO: 140, SEQ ID NO: 141 and SEQ ID NO: 142, SEQ ID NO: 143 and SEQ ID NO: 144, SEQ ID NO: 145 and SEQ ID NO: 146, SEQ ID NO: 147 and SEQ ID NO: 148, SEQ ID NO: 149 and SEQ ID NO: 150, SEQ ID NO: 151 and SEQ ID NO: 152, SEQ ID NO: 153 and SEQ ID NO: 154, SEQ ID NO: 155 and SEQ ID NO: 156, SEQ ID NO: 157 and SEQ ID NO: 158, SEQ ID NO: 159 and SEQ ID NO: 160, SEQ ID NO: 161 and SEQ ID NO: 162, SEQ ID NO: 163 and SEQ ID NO: 164, SEQ ID NO: 165 and SEQ ID NO: 166, SEQ ID NO: 167 and SEQ ID NO: 168, SEQ ID NO: 169 and SEQ ID NO: 170, SEQ ID NO: 171 and SEQ ID NO: 172, SEQ ID NO: 173 and SEQ ID NO: 174, and SEQ ID NO: 175 and SEQ ID NO: 176 to detect the mutation of KDMSC; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 177 and SEQ ID NO: 178, and SEQ ID NO: 179 and SEQ ID NO: 180 to detect the mutation of KDM6A; at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 181 and SEQ ID NO: 182, and SEQ ID NO: 183 and SEQ ID NO: 184 to detect the mutation of LRP12; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 185 and SEQ ID NO: 186, SEQ ID NO: 187 and SEQ ID NO: 188, SEQ ID NO: 189 and SEQ ID NO: 190, and SEQ ID NO: 191 and SEQ ID NO: 192 to detect the mutation of NCOA6; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 193 and SEQ ID NO: 194, SEQ ID NO: 195 and SEQ ID NO: 196, and SEQ ID NO: 197 and SEQ ID NO: 198 to detect the mutation of NHS; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 199 and SEQ ID NO: 200, SEQ ID NO: 201 and SEQ ID NO: 202, and SEQ ID NO: 203 and SEQ ID NO: 204 to detect the mutation of RGAG1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 205 and SEQ ID NO: 206, SEQ ID NO: 207 and SEQ ID NO: 208, SEQ ID NO: 209 and SEQ ID NO: 210, SEQ ID NO: 211 and SEQ ID NO: 212, and SEQ ID NO: 213 and SEQ ID NO: 214 to detect the mutation of SCAF1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 215 and SEQ ID NO: 216, SEQ ID NO: 217 and SEQ ID NO: 218, and SEQ ID NO: 219 and SEQ ID NO: 220 to detect the mutation of SH3TC1; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 221 and SEQ ID NO: 222, SEQ ID NO: 223 and SEQ ID NO: 224, SEQ ID NO: 225 and SEQ ID NO: 226, and SEQ ID NO: 227 and SEQ ID NO: 228 to detect the mutation of TBC1D8B; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 229 and SEQ ID NO: 230, SEQ ID NO: 231 and SEQ ID NO: 232, SEQ ID NO: 233 and SEQ ID NO: 234, SEQ ID NO: 235 and SEQ ID NO: 236, SEQ ID NO: 237 and SEQ ID NO: 238, SEQ ID NO: 239 and SEQ ID NO: 240, SEQ ID NO: 241 and SEQ ID NO: 242, SEQ ID NO: 243 and SEQ ID NO: 244, and SEQ ID NO: 245 and SEQ ID NO: 246 to detect the mutation of TET2; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 247 and SEQ ID NO: 248, SEQ ID NO: 249 and SEQ ID NO: 250, and SEQ ID NO: 251 and SEQ ID NO: 252 to detect the mutation of TEX13A; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 253 and SEQ ID NO: 254 to detect the mutation of ULK3; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 255 and SEQ ID NO: 256, SEQ ID NO: 257 and SEQ ID NO: 258, and SEQ ID NO: 259 and SEQ ID NO: 260 to detect the mutation of WNK3; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 261 and SEQ ID NO: 262 to detect the mutation of ARSF; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 263 and SEQ ID NO: 264, SEQ ID NO: 265 and SEQ ID NO: 266, SEQ ID NO: 267 and SEQ ID NO: 268, and SEQ ID NO: 269 and SEQ ID NO: 270 to detect the mutation of CFP; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 271 and SEQ ID NO: 272 to detect the mutation of FAM47A; at least one primer set selected from the group consisting of base sequence pairs set forth in SEQ ID NO: 273 and SEQ ID NO: 274, and SEQ ID NO: 275 and SEQ ID NO: 276 to detect the mutation of PHF16; a primer set consisting of base sequence pairs set forth in SEQ ID NO: 277 and SEQ ID NO: 278 to detect the mutation of ZNF449; and at least one primer set selected from base sequence pairs set forth in SEQ ID NO: 279 and SEQ ID NO: 280, and SEQ ID NO: 281 and SEQ ID NO: 282 to detect the mutation of SCRN1.

The kit of the present invention thus manufactured is very economical because a lot of time and cost may be save, compared to typical gene mutation search methods known in the art. Several days or Several months are averagely taken to search for one gene thoroughly using the conventional gene mutation search methods such as single strand conformational polymorphism (SSCP), a protein truncation test (PTT), cloning, direct sequencing, and the like. Also, the gene mutation may be rapidly and simply examined accurately using the next-generation sequencing (NGS) method. When the mutation is checked using conventional analytical methods such as SSCP, cloning, direct sequencing, restriction fragment length polymorphism (RFLP), and the like, approximately one month is taken to complete the check. On the other hand, when the kit of the present invention is used and a DNA test sample is prepared, results may be obtained within approximately 10 to 11 hours. Because a primer set capable of detecting the mutation of the gene is stacked in one chip, the time and cost may be saved compared to the conventional methods. Because less than half the reagents' cost per experiment is averagely consumed compared to the conventional methods, a higher cost saving effect may be expected in consideration of the researchers' labor costs.

2. Method of Providing Information Required to Diagnose Prognosis of Kidney Cancer Using Survival-Specific Mutant Gene

According to another aspect of the present invention, there is provided a method of providing information required to verify a difference in therapeutic effect against kidney cancer according to the gender of a patient with kidney cancer. Here, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer whose gender is identified; amplifying the DNA test sample using the kit; determining whether or not there is a gender-specific marker specific to a gender group of target patients from the results of amplification; treating the patient with kidney cancer, in which the gender-specific marker is identified, with any candidate material for treating kidney cancer or healing the patient with kidney cancer using any method; and choosing any candidate material for treating kidney cancer or any method of treating kidney cancer as a therapeutic candidate material or a therapeutic method, which is suitable for the gender group of patients with kidney cancer in which the gender-specific marker is identified, when the any candidate material or the any method is used to treat kidney cancer.

According to still another aspect of the present invention, there is provided a method of providing information required to diagnose prognosis of kidney cancer according to the gender of a patient with kidney cancer. Here, the method includes preparing a DNA test sample from a sample of a patient with kidney cancer; amplifying the DNA test sample using the kit; and determining whether or not there is a gender-specific marker from the results of amplification.

The ‘kit for diagnosing prognosis of kidney cancer’ is as described in ‘1. gender-specific mutant genes in patient with kidney cancer and primer sets capable of detecting the mutant genes’, and thus a specific description thereof is omitted.

The any candidate material for treating kidney cancer may be a therapeutic agent generally used to treat kidney cancer, or a novel material whose therapeutic effect against kidney cancer is not known, but the present invention is not limited thereto. It may be determined whether or not the any therapeutic candidate material has a therapeutic effect on a certain group of patients by treating a patient with kidney cancer having a gender-specific marker with the therapeutic candidate material to check the therapeutic effect. When the therapeutic candidate material has a therapeutic effect against kidney cancer, it may be predicted that the therapeutic candidate material has a high therapeutic effect when the therapeutic candidate material is applied to a group of patients having the same gender-specific marker, thereby providing useful information to determine a therapeutic strategy. Also, when a therapeutic effect is not exerted by the use of the any therapeutic candidate material, the unnecessary treatment needs not to be performed by suspending the therapy on the group of patients having the same gender-specific marker. Therefore, a therapeutic strategy may be effectively designed.

Any method of treating kidney cancer may also be applied instead of the any therapeutic candidate material. After verifying a therapeutic effect in a group of patients having a certain gender-specific marker, it may be determined whether or not the method is applied to the group of patients having the same gender-specific marker. When the therapeutic effect is verified in the group of patients having the gender-specific marker, the any therapeutic candidate material and the any method of treating kidney cancer may be used together.

The term ‘sample’ used herein includes any biological specimen obtained from a patient. The sample includes whole blood, plasma, serum, red blood cells, white blood cells (for example, peripheral blood mononuclear cells), a ductal fluid, hydrops abdominis, a pleural efflux, a nipple aspirate, a lymph fluid (for example, disseminated tumor cells of lymph nodes), a bone marrow aspirate, saliva, urine, feces (that is, stool), phlegm, a bronchial lavage fluid, tear, a fine needle aspirate (for example, collected by random mammary fine needle aspiration), any other bodily fluids, a tissue sample (for example, a tumor tissue), for example, a tumor biopsy (for example, an aspiration biopsy) or a lymph node (for example, a sentinel lymph node biopsy), a tissue sample (for example, a tumor tissue), for example, a surgical resection of tumor, and cell extracts thereof. In some embodiments, the sample is whole blood or some components thereof, for example, plasma, serum or cell pellets. In another embodiment, the sample is obtained by isolating circulating cells of a solid tumor from the whole blood or cell fractions thereof using any techniques known in the related art. In still another embodiment, the sample is, for example, a formalin-fixed paraffin-embedded (FFPE) tumor tissue sample from a solid tumor such as colon cancer.

In certain embodiments, the sample is a tumor lysate or extract prepared from a frozen tissue obtained from a target having colon cancer.

The term ‘patient’ generally includes a human, and may also include other animals, for example, other primates, rodents, dogs, cats, horses, sheep, pigs, and the like.

The term ‘subject’ includes targets excluding a human, which are diagnosed with kidney cancer or suspected to have kidney cancer.

The method may be used to predict an overall survival rate or disease-free survival rate of the patient with kidney cancer.

In the present invention, the term ‘overall survival rate’ includes clinical endpoints recorded for patients who are diagnosed with a disease, for example, cancer or alive for a predetermined period after treatment of the disease, and refers to a survival probability of the patients regardless of the relapse of cancer.

In the present invention, the term ‘disease-free survival rate (DFS)’ includes a survival period of a patient without the relapse of cancer after treatment of a certain disease (for example, cancer).

According to the present invention, the presence of mutations of the gene of the present invention in a sample of a patient with kidney cancer may be analyzed to verify what the prognosis of a subject having a target test sample is for cancer. Also, such a method may be established by comparing overall survival rates or disease-free survival rates of control subjects who are known to have a good prognosis and have no mutations. In the present invention, the subject known to have a good prognosis refers to a subject who has no family histories such as metastasis, relapse, death, and the like after the onset of cancer.

The sample of the subject suspected to have cancer refers to a test sample of a subject or a tissue which already develops cancer or tumor or is expected to develop cancer or tumor, that is, a target test sample used to diagnose the prognosis of cancer or tumor.

The gender-specific marker may be a mutation of a gene coding for one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1. In females of the patients with kidney cancer, the gender-specific marker may be a mutation of a gene coding for one selected from the group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1. In males of the patients with kidney cancer, the gender-specific marker may be a mutation of a gene coding for TET2.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may be used to predict the overall survival rate or disease-free survival rate of the patient with kidney cancer. For example, the method may further include judging that the survival rate of the patient with kidney cancer is not good or that a relapse rate of kidney cancer in the patient with kidney cancer is high when the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1, and the patient with kidney cancer is female.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may further include judging that the survival rate of the patient with kidney cancer is not good when the gender of the patient with kidney cancer is female and the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, and ZNF449, and the patient with kidney cancer is male.

The method of providing information required to diagnose the prognosis of kidney cancer according to the gender of the patient with kidney cancer may further include judging that the relapse rate of kidney cancer in the patient with kidney cancer is high when the gender of the patient with kidney cancer is female and the mutation is identified in the gene coding for one selected from the group consisting of ACSS3, ARSF, CFP, FAM47A, ZNF449, and SCRN1.

As described above, the mutation of at least one gene selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1 is used as the mutation of the gene of the present invention to verify that there is a difference in gene mutations according to the gender of a patient who develops cancer, particularly kidney cancer, but this fact is still unknown. Also, the mutation of at least one gene selected from a gene group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 may be used to diagnose the prognosis of cancer, particularly kidney cancer, in a patient having a certain gender, but this fact is also still unknown. Further, there is no report on the fact that the overall survival rate or disease-free survival rate may be different in each of the genes. The present inventors have first found that the mutation of the genes may be used as a diagnostic marker capable of predicting a difference in therapeutic effect against kidney cancer or diagnosing the prognosis of the patient with kidney cancer according to the gender of the patient with kidney cancer.

The method for providing information required to predict a difference in therapeutic effect against kidney cancer according to the gender of the patient with kidney cancer according to the present invention may be used to diagnose a gene mutation in kidney cancer based on the gender, increase the survival rate of the patient with kidney cancer, or reduce the relapse rate of kidney cancer. Because the therapeutic effect against kidney cancer may be predicted and the survival rate of the patient with kidney cancer or the relapse rate of kidney cancer may be predicted using the information on the gene mutation which varies depending on the gender of the patient who develops kidney cancer, the method for diagnosing the prognosis of kidney cancer according to the present invention may be used to screen therapeutic agents suitable for each patient and select therapeutic methods so as to provide information, thereby effectively designing a therapeutic strategy for kidney cancer.

MODE FOR INVENTION

Hereinafter, the present invention will be described in further detail with reference to examples and experimental examples thereof.

However, it should be understood that the following examples are just preferred examples for the purpose of illustration only and is not intended to limit or define the scope of the invention.

Example 1 Acquisition of Genetic Information and Clinical Information

To check whether the genes of (ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1) may be used as a kidney cancer marker according to the gender of a patient with kidney cancer, the data on the relapse, metastasis, death, and observation time of 417 patients with clear cell renal cell carcinoma whose genetic information and clinical information were all secured were obtained from The Cancer Genome Atlas (TCGA), and used for analyses. The following Table 1 lists the data on the relapse, metastasis, and death of the patients with clear cell renal cell carcinoma.

TABLE 1 Total Gender Number of Ratio Male Female patients (%) Relapse 0 148 (54.6%) 81 (55.5%) 229 55.2% 1 77 (28.4%) 32 (21.9%) 109 26.1% Not 46 (17.0%) 33 (22.6%) 79 18.7% detected Metas- 0 224 (82.7%) 127 (87.0%) 351 84.2% tasis 1 47 (17.3%) 19 (13.0%) 66 15.8% Death 0 181 (66.8%) 89 (61.0%) 270 65.0% 1 90 (33.2%) 57 (39.0%) 147 35.0% Total number 271 146 417 of patients

Example 2 Confirmation of Usability as Gender-Specific Marker

417 patients were divided into two groups based on the gender thereof to check a correlation between of the gender and the mutations of the candidate genes in Example 1 using three feature selection methods (Information Gain, Chi-Square, and MR). Mutation positions of the genes are listed in the following Tables 2 to 6.

TABLE 2 Accession AA Copy Mutation Start End Gene No. change Type # COSMIC Assessor Chr Pos Pos Ref Var ACSS3 NM_024560.3 R634* Nonsense Diploid 4 chr12 81647354 81647354 C T X152_splice Splice Gain chr12 81503485 81503485 T C G268D Missense Gain 1 Low chr12 81536908 81536908 G A ADAM21 NM_003813.3 N265Y Missense ShallowDel 2 Medium chr14 70925009 70925009 A T R408C Missense Diploid 3 Medium chr14 70925438 70925438 C T T589S Missense Diploid 1 Low chr14 70925981 70925981 A T I161V Missense Diploid 3 Low chr14 70924697 70924697 A G AFF2 NM_002025.3 S770F Missense DeepDel 1 Low chr23 148037884 148037884 C T P513H Missense Diploid 1 Medium chr23 148035250 148035250 C A T640N Missense Gain 1 Low chr23 148037494 148037494 C A I149K Missense Diploid 1 Neutral chr23 147743694 147743694 T A I149K Missense Diploid 1 Neutral chr23 147743694 147743694 T A I149K Missense Diploid 1 Neutral chr23 147743694 147743694 T A ALG13 NM_001099922.2 P925T Missense Diploid Low chr23 110987973 110987973 C A L195Pfs*23 FS del Diploid chr23 110951455 110951455 T — V456E Missense Diploid Medium chr23 110964871 110964871 T A BAP1 NM_004656.3 M1? Nonstart ShallowDel 6 chr3 52443894 52443894 T C G128* Nonsense ShallowDel 2 chr3 52441470 52441470 C A E402* Nonsense ShallowDel chr3 52438515 52438515 C A E283Gfs*52 FS del ShallowDel 1 chr3 52439864 52439864 T — V335Efs*56 FS del ShallowDel 1 chr3 52439219 52439238 GCTG — CCTG GAGG CTTC ACCA Q253* Nonsense ShallowDel 2 chr3 52440295 52440295 G A Q267* Nonsense ShallowDel 1 chr3 52439913 52439913 G A

TABLE 3 Accession AA Copy Mutation Start End Gene No. change Type # COSMIC Assessor Chr Pos Pos Ref Var BAP1 NM_004656.3 S460* Nonsense ShallowDel 3 chr3 52437782 52437782 G C F170V Missense ShallowDel 4 High chr3 52441262 52441262 A C K711Sfs*25 FS del ShallowDel 1 chr3 52436362 52436362 T — Y627* Nonsense ShallowDel 1 chr3 52437163 52437163 G C R717Gfs*19 FS del ShallowDel 1 chr3 52436345 52436345 G — X23_splice Splice ShallowDel chr3 52443729 52443729 C T S279* Nonsense ShallowDel 1 chr3 52439876 52439876 G T BAP1 NM_004656.3 R60* Nonsense DeepDel 4 chr3 52442567 52442567 G A M1? Nonstart ShallowDel 6 chr3 52443892 52443892 C T M1? Nonstart ShallowDel 6 chr3 52443892 52443892 C T R700Gfs*36 FS del ShallowDel 1 chr3 52436397 52436397 C — X41_splice Splice ShallowDel chr3 52443568 52443568 A G Q40* Nonsense ShallowDel 2 chr3 52443574 52443574 G A Q156* Nonsense ShallowDel 1 chr3 52441304 52441304 G A K626* Nonsense ShallowDel 1 chr3 52437168 52437168 T A D74Efs*4 FS del ShallowDel 1 chr3 52442523 52442523 A — X41_splice Splice ShallowDel chr3 52443568 52443568 A T D407Vfs*23 FS del ShallowDel 2 chr3 52438499 52438499 T — F170C Missense ShallowDel 4 High chr3 52441261 52441261 A C X23_splice Splice ShallowDel chr3 52443623 52443647 ACCT — GCGA TGAG GAAA GGAA AGCA G X311_splice Splice ShallowDel chr3 52439311 52439311 C A E31A Missense ShallowDel 5 High chr3 52443600 52443600 T G N78S Missense ShallowDel 2 Neutral chr3 52442512 52442512 T C N78S Missense ShallowDel 2 Neutral chr3 52442512 52442512 T C L49V Missense ShallowDel 2 High chr3 52442600 52442600 G C D75G Missense ShallowDel 1 Neutral chr3 52442521 52442521 T C S10T Missense ShallowDel 4 High chr3 52443866 52443866 C G N229H Missense ShallowDel 1 Medium chr3 52440367 52440367 T G G109V Missense ShallowDel 1 High chr3 52442023 52442023 C A L17P Missense ShallowDel 1 Medium chr3 52443747 52443747 A G A145G Missense ShallowDel 1 Medium chr3 52441418 52441418 G C K659Del IF del DeepDel chr3 52436801 52436803 CTT — A1061T Missense Diploid 2 Medium chr23 79948521 79948521 C T

TABLE 4 Accession AA Copy Gene No. change Type # COSMIC BRWD3 NM_153252.4 G287A Missense Diploid 1 I1747N Missense Diploid 1 COL4A5 NM_000495.4 P1184L Missense Diploid 1 P756S Missense Diploid 1 P1365S Missense Diploid G1427V Missense Diploid X1510_splice Splice Diploid A1656T Missense Diploid CPEB1 NM_030594.4 S393R Missense Diploid G136V Missense Diploid X499_splice Splice Diploid ERBB2 NM_004448.3 E1114G Missense Diploid 1 S649T Missense Diploid 1 V219I Missense Diploid 1 N388Qfs*14 FS ins Diploid HSP90AA1 NM_001017963.2 D512N Missense ShallowDel 2 H806R Missense Diploid 1 I325T Missense ShallowDel 1 L167V Missense ShallowDel 1 Mutation Start End Gene Assessor Chr Pos Pos Ref Var BRWD3 Neutral chr23 79991541 79991541 C G Neutral chr23 79932277 79932277 A T COL4A5 Medium chr23 107909822 107909822 C T Medium chr23 107849993 107849993 C T Medium chr23 107924995 107924995 C T High chr23 107929324 107929324 G T chr23 107935977 107935977 G T Neutral chr23 107938641 107938641 G A CPEB1 Medium chr15 83221251 83221251 G C Neutral chr15 83226709 83226709 C A chr15 83215272 83215272 C A ERBB2 Low chr17 37883729 37883729 A G Low chr17 37876087 37876087 G C Neutral chr17 37866350 37866350 G A chr17 37871549 37871550 — C HSP90AA1 High chr14 102550300 102550300 C T High chr14 102548486 102548486 T C High chr14 102551690 102551690 A G Medium chr14 102552583 102552583 G C

TABLE 5 Accession AA Copy Gene No. change Type # COSMIC IRAK1 NM_001569.3 Q280* Nonsense Diploid 1 V548M Missense Diploid 1 Q584K Missense Diploid 1 KDM5C NM_004187.3 R681* Nonsense Diploid 3 Q813* Nonsense Diploid 2 E1152K Missense Diploid 1 X321_splice Splice Diploid T471Vfs*5 FS del Diploid R1458W Missense Diploid 1 G536W Missense Diploid 1 E284* Nonsense Diploid 1 Q1427Pfs*50 FS del Diploid 1 C730R Missense Diploid 2 E592V Missense Diploid 1 E798* Nonsense Diploid 1 C512W Missense Diploid 1 Y639* Nonsense Diploid 1 S1110* Nonsense Diploid 1 E122Vfs*14 FS del Diploid 1 K459* Nonsense Diploid 1 E1131Sfs*16 FS del Diploid 1 C730F Missense Diploid 2 H988Tfs*18 FS del Diploid 1 H733P Missense Diploid 1 P27Lfs*46 FS del Diploid 1 F56Cfs*18 FS del Diploid 1 D1414Efs*54 FS del Diploid 1 R215* Nonsense Diploid 1 G845Rfs*2 FS del ShallowDel Mutation Start End Gene Assessor Chr Pos Pos Ref Var IRAK1 chr23 153283528 153283528 G A Neutral chr23 153278782 153278782 C T Low chr23 153278674 153278674 G T KDM5C chr23 53230752 53230752 G A chr23 53227751 53227751 G A Medium chr23 53223905 53223905 C T chr23 53244975 53244975 A G chr23 53240028 53240031 GGTA — Low chr23 53222460 53222460 G A High chr23 53239736 53239736 C A chr23 53245090 53245090 C A chr23 53222653 53222656 GGCT — Medium chr23 53228214 53228214 A G High chr23 53231127 53231127 T A chr23 53227796 53227796 C A High chr23 53239905 53239905 G C chr23 53230876 53230877 — T chr23 53224222 53224222 G C chr23 53247129 53247135 CCAC — CTT chr23 53240705 53240705 T A chr23 53224160 53224160 C — Medium chr23 53228213 53228213 C A chr23 53225887 53225887 G — Medium chr23 53228204 53228204 T G chr23 53253992 53253992 G — chr23 53250081 53250082 AA — chr23 53222684 53222694 TGTG — GTTC TCA chr23 53246339 53246339 T A chr23 53227036 53227042 GTAGACC —

TABLE 6 Accession AA Copy Gene No. change Type # COSMIC KDM6A NM_021140.3 A30V Missense Diploid 1 A1246Pfs*19 FS del Diploid V156Del IF del ShallowDel LRP12 NM_013437.4 S622L Missense Diploid 1 E639K Missense Diploid 2 V671I Missense Gain 1 NCOA6 NM_001242539.2 G164E Missense Diploid 1 N877I Missense Gain 1 N864Y Missense Gain 1 V1444A Missense Diploid 1 H832Sfs*47 FS ins Gain NHS NM_198270.3 C360R Missense Diploid P1107A Missense Diploid 1 D1069H Missense Diploid 2 RGAG1 NM_020769.2 A1015G Missense Diploid 1 M858V Missense Diploid 1 G1053R Missense Diploid 1 SCAF1 NM_021228.2 A219Sfs*11 FS ins ShallowDel P211Tfs*19 FS ins Diploid P211Tfs*19 FS ins Diploid A216Pfs*94 FS del Diploid Mutation Start End Gene Assessor Chr Pos Pos Ref Var KDM6A Medium chr23 44732886 44732886 C T chr23 44949174 44949174 A — chr23 44879876 44879878 GGT — LRP12 Low chr8 105503616 105503616 G A Neutral chr8 105503566 105503566 C T Neutral chr8 105503470 105503470 C T NCOA6 Low chr20 33356290 33356290 C T Low chr20 33337368 33337368 T A Neutral chr20 33337408 33337408 T A Neutral chr20 33329729 33329729 A G chr20 33337505 33337506 — G NHS Low chr23 17742451 17742451 T C Low chr23 17745608 17745608 C G Medium chr23 17745494 17745494 G C RGAG1 Low chr23 109696889 109696889 C G Neutral chr23 109696417 109696417 A G Low chr23 109697002 109697002 G C SCAF1 chr19 50154294 50154295 — C chr19 50154270 50154271 — C chr19 50154270 50154271 — C chr19 50154291 50154294 TGCA —

TABLE 7 Accession AA Copy Mutation Start End Gene No. change Type # COSMIC Assessor Chr Pos Pos Ref Var SH3TC1 NM_018986.4 A375V Missense Diploid 1 Neutral chr4 8224578 8224578 C T R238Sfs*38 FS del Diploid chr4 8218768 8218768 G — L180F Missense Diploid 1 Neutral chr4 8217896 8217896 G T TBC1D8B NM_017752.2 G1059V Missense Diploid 2 Neutral chr23 106117008 106117008 G T A614T Missense ShallowDel 1 Medium chr23 106093257 106093257 G A S861* Nonsense Gain 1 chr23 106109183 106109183 C G Y815F Missense Diploid J Medium chr23 106109045 106109045 A T Y815F Missense Diploid 3 Medium chr23 106109045 106109045 A T Y815F Missense ShallowDel 3 Medium chr23 106109045 106109045 A T TET2 NM_001127208.2 Q317K Missense ShallowDel 1 Low chr4 106156048 106156048 C A K326* Nonsense Diploid 1 chr4 106156075 106156075 A T L757V Missense Diploid Neutral chr4 106157368 106157368 C G V449E Missense Diploid Low chr4 106156445 106156445 T A N1714K Missense Diploid 1 Medium chr4 106196809 106196809 T G D194E Missense Diploid 1 Low chr4 106155681 106155681 C A N1390H Missense Diploid 1 Medium chr4 106190890 106190890 A C R1451Q Missense Diploid 2 Medium chr4 106193890 106193890 G A M600I Missense ShallowDel 1 Neutral chr4 106156899 106156899 G A P554S Missense ShallowDel 1 Neutral chr4 106156759 106156759 C T TEX13A NM_001291277.1 R393S Missense Diploid Medium chr23 104463697 104463697 C A X199_splice Splice Diploid 2 chr23 104464282 104464282 C — X199_splice Splice Diploid 2 chr23 104464282 104464282 C — Y257D Missense Diploid Low chr23 104464107 104464107 A C ULK3 NM_001099436.3 Q81Sfs*41 FS del Diploid chr15 75134624 75134624 A — D79H Missense Diploid Medium chr15 75134629 75134629 C G L77V Missense Diploid Low chr15 75134635 75134635 G C WNK3 NM_001002838.3 S865* Nonsense Diploid 1 chr23 54276546 54276546 G T E537G Missense Diploid 1 Low chr23 54321069 54321069 T C Y589* Nonsense Diploid 1 chr23 54319687 54319687 A T

The correlation between the mutagenesis of the candidate genes and the gender of the patients with kidney cancer was confirmed with respect to each the gender groups. A P-value of less than 0.05 was considered to be statistically significant. The following Tables 8 and 11 list information on the related candidate genes (M0: No distant metastasis, and M1: Distant metastasis).

TABLE 8 Total No. of patients with identified Fisher's Mutation type Gender gene Exact Missense Missense In- Metastasis Metastasis M F mutations (P-value) Mutation(%) Truncating (P) (D) frame Cytoband M0 M1 (%) ACSS3 0 3 3 0.042 0.72% 2 1 0 0 12q21.31 1 2 66.70% ADAM21 0 4 4 0.015 0.96% 0 4 0 0 14q24.1 4 0 0.00% AFF2 1 5 6 0.022 1.44% 0 6 0 0 Xq28 5 1 16.70% ALG13 0 3 3 0.042 0.72% 1 2 0 0 Xq23 3 0 0.00% AOC2 2 2 4 0.614 0.96% 3 1 0 0 17q21 4 0 0.00% AR 0 1 1 0.35 0.24% 0 1 0 0 Xq12 1 0 0.00% ARSF 0 1 1 0.35 0.24% 0 1 0 0 Xp22.3 1 0 0.00% ASUN 1 2 3 0.281 0.72% 1 2 0 0 12p11.23 2 1 33.30% ASXL2 2 4 6 0.19 1.44% 4 1 0 1 2p24.1 4 2 33.30% ASXL3 7 0 7 0.102 1.68% 0 7 0 0 18q12.1 4 3 42.90% AVPR2 0 2 2 0.122 0.48% 0 2 0 0 Xq28 2 0 0.00% BAP1 12 25 37 <0.001 8.87% 25 8 3 1 3p21.1 26 11 29.70% BCOR 2 0 2 0.544 0.48% 1 1 0 0 Xq25-q26.1 1 1 50.00% BHLHB9 3 0 3 0.555 0.72% 0 3 0 0 Xq23 3 0 0.00% BRWD3 0 3 3 0.042 0.72% 0 3 0 0 Xq21.1 3 0 0.00% CDCA7 0 2 2 0.122 0.48% 0 2 0 0 2q31.1 2 0 0.00% CELSR1 7 0 7 0.102 1.68% 3 4 0 0 22q13.31 5 2 28.60% CFP 1 3 4 0.126 0.96% 1 3 0 0 Xp11.4 3 1 25.00% CLN8 0 2 2 0.122 0.48% 0 2 0 0 8p23 2 0 0.00%

TABLE 9 Total No. of patients with identified Fisher's Mutation type Gender gene Exact Mutation Missense Missense In- Metastasis Metastasis M F mutations (P-value) (%) Truncating (P) (D) frame Cytoband M0 M1 (%) COL4A5 1 5 6 0.022 1.44% 1 5 0 0 Xq22 5 1 16.70% CPEB1 0 3 3 0.042 0.72% 1 2 0 0 15q25.2 2 1 33.30% CYLC1 0 2 2 0.122 0.48% 0 2 0 0 Xq21.1 2 0 0.00% DYSF 2 4 6 0.19 1.44% 2 3 0 1 2p13.2 4 2 33.30% ERBB2 0 4 4 0.015 0.96% 1 3 0 0 17q12 4 0 0.00% FAM47A 1 3 4 0.126 0.96% 0 2 0 2 Xp21.1 3 1 25.00% FRMD7 4 0 4 0.302 0.96% 2 2 0 0 Xp22.2 3 1 25.00% FRMPD4 4 0 4 0.302 0.96% 3 1 0 0 Xp22.2 4 0 0.00% GABRQ 2 4 6 0.19 1.44% 2 4 0 0 Xq28 5 1 16.70% GPR45 0 3 3 0.042 0.72% 1 2 0 0 2q12.1 2 1 33.30% HAUS7 2 0 2 0.544 0.48% 0 2 0 0 Xq28 1 1 50.00% HSP90AA1 0 4 4 0.015 0.96% 0 4 0 0 14q32.31 4 0 0.00% IRAK1 0 3 3 0.042 0.72% 1 2 0 0 Xq28 3 0 0.00% ITIH6 0 1 1 0.35 0.24% 0 1 0 0 Xp11.22- 1 0 0.00% p11.21 KDM5C 3 23 26 <0.001 6.24% 18 8 0 0 Xp11.22- 22 4 15.40% p11.21 KDM6A 0 3 3 0.042 0.72% 1 1 0 1 Xp11.2 3 0 0.00% LPAR4 0 2 2 0.122 0.48% 1 1 0 0 Xq21.1 2 0 0.00% LRP12 0 3 3 0.042 0.72% 0 3 0 0 8q22.2 3 0 0.00% MAGEB10 0 2 2 0.122 0.48% 0 2 0 0 Xp21.1 2 0 0.00%

TABLE 10 Total No. of patients with identified Fisher's Gender gene Exact Mutation type M F mutations (P-value) Mutation(%) Truncating MAGEB16 0 2 2 0.122 0.48% 0 MAGED1 2 0 2 0.544 0.48% 0 MAP3K15 1 3 4 0.126 0.96% 2 MED14 4 1 5 0.661 1.20% 1 NBPF10 4 4 8 0.459 1.92% 2 NCOA6 0 4 4 0.015 0.96% 1 NCOR1P1 Null 20p11.1 Null NHS 0 3 3 0.042 0.72% 0 NOX1 2 2 4 0.614 0.96% 2 PABPC3 9 1 10 0.176 2.40% 1 PHF16(JADE3) 0 2 2 0.122 0.48% 0 POTEH-AS1 Null 22q11.1 Null PRRG3 0 2 2 0.122 0.48% 0 RGAG1 0 3 3 0.042 0.72% 0 SCAF1 0 4 4 0.015 0.96% 4 SCRN1 0 2 2 0.122 0.48% 1 SH3TC1 0 3 3 0.042 0.72% 1 SMC1A 0 2 2 0.122 0.48% 1 SYTL4 0 1 1 0.35 0.24% 0 Mutation type Missense Missense In- Metastasis Metastasis (P) (D) frame Cytoband M0 M1 (%) MAGEB16 2 0 0 Xp21.1 2 0 0.00% MAGED1 2 0 0 Xp11.23 2 0 0.00% MAP3K15 2 0 0 Xp22.12 3 1 25.00% MED14 4 0 0 Xp11.4 5 0 0.00% NBPF10 6 0 0 1q21.1 6 2 25.00% NCOA6 3 0 0 20q11.22 4 0 0.00% NCOR1P1 NHS 3 0 0 Xp22.13 3 0 0.00% NOX1 2 0 0 Xq22 4 0 0.00% PABPC3 9 0 0 13q12-ql3 10 0 0.00% PHF16(JADE3) 2 0 0 Xp11.23 2 0 0.00% POTEH-AS1 PRRG3 2 0 0 Xq28 2 0 0.00% RGAG1 3 0 0 Xq23 3 0 0.00% SCAF1 0 0 0 19q13.33 3 1 25.00% SCRN1 1 0 0 7p14.3 1 1 50.00% SH3TC1 2 0 0 4p16.1 3 0 0.00% SMC1A 1 0 0 Xp11.22- 2 0 0.00% p11.21 SYTL4 1 0 0 Xq21.33 1 0 0.00%

TABLE 11 Total No. of patients with identified Fisher's Mutation type Gender gene Exact Mutation Missense Missense In- Metastasis Metastasis M F mutations (P-value) (%) Truncating (P) (D) frame Cytoband M0 M1 (%) TBC1D8B 1 5 6 0.022 1.44% 1 5 0 0 Xq22.3 6 0 0.00% TET2 9 0 9 0.03 2.16% 1 8 0 0 4q24 3 6 66.70% TEX13A 0 4 4 0.015 0.96% 2 2 0 0 Xq22.3 4 0 0.00% TFDP3 1 2 3 0.281 0.72% 0 3 0 0 Xq26.2 3 0 0.00% TRO 0 2 2 0.122 0.48% 1 1 0 0 Xp11.22- 2 0 0.00% p11.21 ULK3 0 3 3 0.042 0.72% 1 2 0 0 15q24.1 3 0 0.00% USP51 1 4 5 0.53 1.20% 1 4 0 0 Xp11.21 3 2 40.00% WNK3 0 3 3 0.042 0.72% 2 1 0 0 Xp11.22 2 1 33.30% ZMYM3 1 1 2 1 0.48% 0 2 0 0 Xq13.1 2 0 0.00% ZNF318 2 5 7 0.054 1.68% 2 5 0 0 6p21.1 6 1 14.30% ZNF449 0 1 1 0.35 0.24% 0 1 0 0 Xq26.3 1 0 0.00%

From the analysis results, it was confirmed that there were the genes whose P-values were shown to be greater than or equal to 0.05 compared to the other groups even when the genes had mutations in each of the gender groups, and also confirmed that there were the genes whose P-values were shown to be less than 0.05 while the genes had the mutations. Because the mutant genes whose P-values were less than 0.05 compared to the other groups correlated with the certain gender group compared to the other groups, the mutant genes were defined as gender-specific genes. For example, it can be seen that there were a large total number of patients in which AOC2, AR, and ARSF were mutated, but the AOC2, AR, and ARSF mutants had a high P-value of 0.05 or more, there was no correlation between the gender of the patients and the mutations of these genes. On the other hand, it was confirmed that, because the ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, and WNK3 genes has a P-value of less than 0.05 in comparison between the groups, there was a correlation between the gender of the patients and the mutagenesis of these genes.

FIG. 1 shows the results of analyzing the correlation between the gender of patients and the mutations of genes. As shown in FIG. 1, it was confirmed that there were a larger number of patients having the mutant genes in the female groups than in the male groups in the case of the ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, and WNK3 genes, and there were a larger number of patients having the mutant gene in the male groups than in the female groups in the case of the TET2 gene.

From the results, it can be seen that the mutations of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TEX13A, ULK3, and WNK3 were able to be used as the markers specific to the female groups, and that the mutation of TET2 was able to be used as the marker specific to the male groups.

Example 3 Confirmation of Applicability as Survival-Specific Markers According to Gender

It was confirmed whether there were survival-specific mutant genes among the candidate genes according to the gender. The analyses were performed in the same manner as in Example 2. Mutation positions of the respective genes are listed in Table 12.

TABLE 12 Accession AA Copy Gene No. change Type # COSMIC ACSS3 NM_024560.3 R634* Nonsense Diploid 4 X152_splice Splice Gain G268D Missense Gain 1 ALG13 NM_001099922.2 P925T Missense Diploid L195Pfs*23 FS del Diploid V456E Missense Diploid ARSF NM_001201538.1 I42F Missense Diploid 1 CFP NM_001145252.1 S27L Missense Diploid 2 R359Q Missense Diploid 1 E135K Missense Diploid 1 E323Gfs*34 FS ins Gain 1 FAM47A NM_203408.3 R505H Missense ShallowDel 3 E507Q Missense ShallowDel 6 L235_H246Del IF del Diploid L235_H246Del IF del Diploid KDM6A NM_021140.3 A30V Missense Diploid 1 A1246Pfs*19 FS del Diploid V156Del IF del ShallowDel PHF16(JADE3) NM_001077445.2 K656Q Missense Diploid R207W Missense ShallowDel ZNF449 NM_152695.5 F183I Missense Diploid 1 SCRN1 NM_001145514.1 D427Y Missense Gain A257Cfs*34 FS ins Diploid Mutation Start End Gene Assessor Chr Pos Pos Ref Var ACSS3 chr12 81647354 81647354 C T chr12 81503485 81503485 T C Low chr12 81536908 81536908 G A ALG13 Low chr23 110987973 110987973 C A chr23 110951455 110951455 T — Medium chr23 110964871 110964871 T A ARSF Medium chr23 2990179 2990179 A T CFP Medium chr23 47489070 47489070 G A Low chr23 47485783 47485783 C T Low chr23 47487501 47487501 C T chr23 47485891 47485892 — C FAM47A Neutral chr23 34148882 34148882 C T Low chr23 34148877 34148877 C G chr23 34149658 34149693 ATGG — GACA CTCC AGTC TCTG GAGG CTCC GGGC GGAG chr23 34149658 34149693 ATGG — GACA CTCC AGTC TCTG GAGG CTCC GGGC GGAG KDM6A Medium chr23 44732886 44732886 C T chr23 44949174 44949174 A — chr23 44879876 44879878 GGT — PHF16(JADE3) Low chr23 46917973 46917973 A C Medium chr23 46887437 46887437 C T ZNF449 Low chr23 134483227 134483227 T A SCRN1 Medium chr7 29963599 29963599 C A chr7 29980329 29980330 — C

An overall survival Kaplan-Meier estimate and a disease-free survival Kaplan-Meier estimate were calculated using a Kaplan-Meier survival analysis method (Spss 21). The 417 target patients volunteered in Example 1 were divided into surviving patients (270) and dead patients (147), and comparative analyses thereof were performed. The overall survival Kaplan-Meier estimate or the disease-free survival Kaplan-Meier estimate was calculated based on the clinical information (occurrence of events (death or relapse), and observation time) on the patients volunteered in Example 1 using the Kaplan-Meier survival analysis method. The event was defined as ‘death’ for the overall survival Kaplan-Meier estimate, and the event was defined as ‘relapse’ for the disease-free survival Kaplan-Meier estimate. To verify whether the mutagenesis in each of the genes correlated with the death of the patients from kidney cancer or the relapse of kidney cancer, the correlation between the mutagenesis and the overall survival Kaplan-Meier estimate, and the correlation between the mutagenesis and the disease-free survival Kaplan-Meier estimate were confirmed, based on the event times of the respective groups obtained in the Kaplan-Meier survival analysis method, using a log rank test. A P-value of less than 0.05 was considered to be statistically significant. Cases with alterations in the query genes of the present invention were used as the experimental groups, and a case without alterations in the query genes of the present invention was used as the control. A median months survival refers to a median value when the survival estimates of the patients from the corresponding groups were listed. A gradient of the survival curve obtained by the Kaplan-Meier survival analysis method was determined by the survival estimates.

To check whether the mutagenesis in each of the candidate genes correlated with the survival rate of the patients with kidney cancer, who had a certain gender, the genetic information on the 417 patient with kidney cancer obtained in Example 1 was analyzed. The gender of the patients in which the mutations of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes were identified was listed in Table 13.

TABLE 13 Gender group Total number of patients with M F identified gene mutations ACSS3 0 3 3 ALG13 0 3 3 ARSF 0 1 1 CFP 1 3 4 FAM47A 1 3 4 KDM6A 0 3 3 PHF16 0 2 2 ZNF449 0 1 1 SCRN1 0 2 2

As shown in FIGS. 2 to 10, it can be seen that, because the probability of the null hypothesis being true was shown to be greater than or equal to 99.5% when it is assumed that the mutagenesis of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes correlated with the survival rates of the females of the patients with kidney cancer in comparison between the groups, that is, the probability of the null hypothesis being false was shown to be less than 0.5%, there was the correlation between the mutagenesis of the ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 genes and the survival rate of the female patients of the patients with kidney cancer (see information on ‘Gender group’ and information on ‘Total number of patients with identified gene mutations’ listed in Table 13).

Some mutant genes whose P-values were shown to be greater than or equal to 0.05, the value of which was considered to be insignificant, when only the correlation between the mutagenesis and the gender was verified in Example 1 had a P-value of less than 0.05, the value of which was considered to be significant, when the correlation between the mutagenesis and the survival rates of the patients with kidney cancer who had a certain gender. For example, the P-value of ARSF was considered to be insignificant only when the correlation between the mutagenesis and the gender was verified in Example 1, but considered to be significant when the correlation between the mutation of ARSF and the survival rates of the patients was compared between the gender groups in this example (see information on ‘Gender group’ of Table 13 and the P-values shown in FIGS. 2 to 15).

The analysis results of survival of the patients with kidney cancer who had the mutant genes are shown in FIGS. 2 to 15.

From the analysis results, as shown in FIG. 2(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ACSS3 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ACSS3 gene was mutated died within 20 months, the patients with kidney cancer in which the ACSS3 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ACSS3 gene was not mutated (red). Referring to FIG. 2(B), it was revealed that at least 50% of the patients with kidney cancer in which the ACSS3 gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the ACSS3 gene was mutated (red). Therefore, it can be seen that the mutation of the ACSS3 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ACSS3 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 3, it was confirmed that at least 50% of the patients with kidney cancer in which the ALG13 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ALG13 gene was mutated died within 20 months, the patients with kidney cancer in which the ALG13 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ALG13 gene was not mutated (red). Therefore, it can be seen that the mutation of the ALG13 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the ALG13 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 4(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ARSF gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ARSF gene was mutated died within 20 months, the patients with kidney cancer in which the ARSF gene was mutated had a survival rate lower than the patients with kidney cancer in which the ARSF gene was not mutated (red). Referring to FIG. 4(B), it was revealed that at least 50% of the patients with kidney cancer in which the ARSF gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the ARSF gene was mutated (red). Therefore, it can be seen that the mutation of the ARSF gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ARSF gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 5(A), it was confirmed that at least 50% of the patients with kidney cancer in which the CFP gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the CFP gene was mutated died within 20 months, the patients with kidney cancer in which the CFP gene was mutated had a survival rate lower than the patients with kidney cancer in which the CFP gene was not mutated (red). Referring to FIG. 5(B), it was revealed that at least 50% of the patients with kidney cancer in which the CFP gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the CFP gene was mutated (red). Therefore, it can be seen that the mutation of the CFP gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the CFP gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 6(A), it was confirmed that at least 50% of the patients with kidney cancer in which the FAM47A gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the FAM47A gene was mutated died within 20 months, the patients with kidney cancer in which the FAM47A gene was mutated had a survival rate lower than the patients with kidney cancer in which the FAM47A gene was not mutated (red). Referring to FIG. 6(B), it was revealed that at least 50% of the patients with kidney cancer in which the FAM47A gene was not mutated did not relapse into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 40 months when the FAM47A gene was mutated (red). Therefore, it can be seen that the mutation of the FAM47A gene was useful as the marker for predicting the survival rate of the patients with kidney cancer and the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the FAM47A gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 7, it was confirmed that at least 50% of the patients with kidney cancer in which the KDM6A gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the KDM6A gene was mutated died within 20 months, the patients with kidney cancer in which the KDM6A gene was mutated had a survival rate lower than the patients with kidney cancer in which the KDM6A gene was not mutated (red). Therefore, it can be seen that the mutation of the KDM6A gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the KDM6A gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 8, it was confirmed that at least 50% of the patients with kidney cancer in which the PHF16 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the PHF16 gene was mutated died within 40 months, the patients with kidney cancer in which the PHF16 gene was mutated had a survival rate lower than the patients with kidney cancer in which the PHF16 gene was not mutated (red). Therefore, it can be seen that the mutation of the PHF16 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer because the patients had a high probability of dying from kidney cancer when the PHF16 gene was mutated and the gender of the patients with kidney cancer was female.

Referring to FIG. 9, it was revealed that at least 50% of the patients with kidney cancer in which the SCRN1 gene did not relapsed into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the SCRN1 gene was mutated (red). Therefore, it can be seen that the mutation of the SCRN1 gene was useful as the marker for predicting the relapse of kidney cancer because the patients had a high probability of relapsing into kidney cancer when the SCRN1 gene was mutated and the gender of the patients with kidney cancer was female.

As shown in FIG. 10(A), it was confirmed that at least 50% of the patients with kidney cancer in which the ZNF449 gene was not mutated survived for 80 months or more (blue). On the other hand, it was confirmed that, because at least 50% of the patients with kidney cancer in which the ZNF449 gene was mutated died within 10 months, the patients with kidney cancer in which the ZNF449 gene was mutated had a survival rate lower than the patients with kidney cancer in which the ZNF449 gene was not mutated (red). Referring to FIG. 10(B), it was revealed that at least 50% of the patients with kidney cancer in which the ZNF449 gene did not relapsed into kidney cancer for 100 months or more (blue), but at least 50% of the patients with kidney cancer relapsed into kidney cancer within 20 months when the ZNF449 gene was mutated (red). Therefore, it can be seen that the mutation of the ZNF449 gene was useful as the marker for predicting the survival rate of the patients with kidney cancer or the relapse of kidney cancer because the patients had a high probability of dying from kidney cancer or relapsing into kidney cancer when the ZNF449 gene was mutated and the gender of the patients with kidney cancer was female.

From the above results, it can be seen that the survival rate of the patients with kidney cancer who had a certain gender was significantly reduced, or the relapse rate of kidney cancer in the patients with kidney cancer was increased when any one gene selected from the group consisting of ACSS3, ALG13, ARSF, CFP, FAM47A, KDM6A, PHF16, ZNF449, and SCRN1 was mutated. Therefore, it can be seen that the prognoses of kidney cancer, particularly the survival of the patients with kidney cancer or the relapse of kidney cancer, were able to be predicted by comparing the gender of the patients to check whether the genes of the present invention were mutated.

Example 4 Manufacture of Chips Capable of Detecting Genes of Examples 2 and 3

Primer sets for detecting mutations of the genes of Examples 2 and 3 were constructed using Ion AmpliSeq Custom and Community Panels (commercially available from Thermo fisher) with reference to https://tools.thermofishercom/content/sfs/manuals/MAN0006735_AmpliSeq_DNA_R NA_LibPrep_UG.pdf. To easily detect the mutations, types of chips were selected and the depth of the chips was enhanced. Specifically, information on a panel to be manufactured was input into Ampliseq.com, and the input information was fed back. Thereafter, the related items were discussed to manufacture a panel equipped with a primer set capable of detecting the mutation. Tables 14 to 21 list the primer sets capable of detecting the mutations of the genes of the present invention.

TABLE 14 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop ACSS3 chr12 31 GGGATAAGATTG 32 GAAGGCTCTAC 8150 8150 8150 8150 CTATCATCTATG AATGAGAATGTA 3404 3433 3537 3566 ACAGT TGCTAT ACSS3 chr12 33 TTCAGTCAGATG 34 ACAGTCATGTG 8153 8153 8153 8153 CTCAGACTTAAA ACTGGGCTTTT 6787 6817 6938 6960 TAGATT ACSS3 chr12 35 CTCTAGATATAA 36 CCATTGACAATG 8164 8164 8164 8164 ATGCAACAGAG GCAGATAAAGC 7268 7297 7411 7436 GAGCAA TG ADAM21 chr14 37 GGGCTTTCGAG 38 TGCTACTTCCTT 7092 7092 7092 7092 GAGTATTAAAAA CTCTGTTAAGCC 4606 4634 4735 4759 TAAGT ADAM21 chr14 39 GTATTTCTTGTT 40 ATGCTGTAGCTG 7092 7092 7092 7092 GTCAACATAGTG GGAAAGACTG 4919 4949 5070 5092 GATTCC ADAM21 chr14 41 CTTAAACCAGG 42 GTCTTGTTCACA 7092 7092 7092 7092 GATCATGTCTGC CTGCTGTACG 5377 5402 5487 5509 AT ADAM21 chr14 43 GATGTCTTTTGT 44 GGCCACACACA 7092 7092 7092 7092 GGGAGAGTTCA GTACCATCTTT 5885 5911 6037 6059 ATG AFF2 chrX 45 TCACCAGGATAA 46 AGTCTGCATCTT 1477 1477 1477 1477 TACCCATCCTTC GTTTGGCTGA 4362 4364 4377 4379 A 3 8 5 7 AFF2 chrX 47 TCGGAGAGCAG 48 CTGTGGGACAG 1480 1480 1480 1480 CTCTGAGT GCAGATCAT 3518 3519 3529 3531 0 9 6 6 AFF2 chrX 49 GGCTTTGAAGC 50 GGGTCATGAAG 1480 1480 1480 1480 ATAAGTTGTCAA CTCCACACTTT 3739 3742 3755 3757 CA 9 4 0 2 AFF2 chrX 51 GCCAAATCCAA 52 AGAGGTTTTTC 1480 1480 1480 1480 GGAAATCTGTG AGGTTCTCATGA 3780 3782 3795 3797 GT TCTC 5 9 2 9 ALG13 chrX 53 TCCGGATACCTG 54 CATCCATTGATG 1109 1109 1109 1109 CATAAGCAAG CCTCATTCAAA 5136 5138 5151 5154 GAC 7 9 5 1 ALG13 chrX 55 GAAGACTAAGG 56 TCCTGTTGATAT 1109 1109 1109 1109 ATTGTGAGTTTG TTCTTTACCTTT 6478 6481 6492 6495 TAGCA TCTGCT 5 3 9 9 ALG13 chrX 57 TCTTTGTTAGTG 58 AGTCTCTCCCA 1109 1109 1109 1109 ATTGCCTCACCA CATCAAGAGCA 8788 8791 8803 8805 T 6 1 4 6

TABLE 15 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop BAP1 chr3 59 GTAGGAGAGAA 60 GTGGAGGCTGA 5243 5243 5243 5243 GAAGACTGAGA GATTGCAAACT 6693 6720 6840 6863 GCACT A BAP1 chr3 61 TTCCAATCAAG 62 GTCGTGGAAGC 5243 5243 5243 5243 AACTTGGCACC CACGGACA 7065 7088 7218 7237 T BAP1 chr3 63 GCCGTGTCTGTA 64 CCATCAACGTC 5243 5243 5243 5243 CTCTCATTGC TTGGCTGAGAA 7674 7696 7808 7830 BAP1 chr3 65 AACCTGGTAGC 66 TTGTCCCAGGA 5243 5243 5243 5243 CTTAGAAAGCT GGAAGAAGACC 8439 8462 8588 8611 G T BAP1 chr3 67 GGGACTTGGCA 68 ATCCCACAGCC 5243 5243 5243 5243 TAATTGTGATTG CTCCCAACAAA 9134 9158 9248 9270 T BAP1 chr3 69 GCTTCACCACTA 70 GGGAGACTGTG 5243 5243 5243 5243 GCTTGGGTTT AGCTTTTCTTGG 9230 9252 9353 9376 BAP1 chr3 71 GGACTTGTTGCT 72 GGGTCTACCCT 5243 5243 5243 5243 GGCTGACTT TTCTCCTCTGA 9836 9857 9948 9970 BAP1 chr3 73 GTATGTTCACGA 74 CGACCGCAGGA 5244 5244 5244 5244 ATCAGAGACAA TCAAGTATGAG 0173 0200 0325 0347 ATGC BAP1 chr3 75 CAGCCTGGCCT 76 CAGGATATCTGC 5244 5244 5244 5244 CATACTTGATC CTCAACCTGAT 0317 0339 0440 0464 G BAP1 chr3 77 CATGGTGCCTAC 78 CCTGAGAAGCA 5244 5244 5244 5244 CATGGTCAAT GAATGGCCTTA 1178 1200 1291 1313 BAP1 chr3 79 CGCACTGCACT 80 GCCAAGGCCCA 5244 5244 5244 5244 AAGGCCATT TAATAGCCATG 1282 1302 1418 1440 BAP1 chr3 81 CACACACCTGG 82 CCCATAGTCCTA 5244 5244 5244 5244 CATGGCTATTA CCTGAGGAGAA 1408 1430 1510 1534 A BAP1 chr3 83 CTGAAACCCTT 84 TTGGTTTCACA 5244 5244 5244 5244 GGTGAAGTCCT GCTGATACCCA 1981 2003 2082 2105 A BAP1 chr3 85 ATCCCACCCTCC 86 CCCAGCCCTGT 5244 5244 5244 5244 AAACAAAGCA ATATGGATTTAT 2453 2475 2601 2627 CTT BAP1 chr3 87 GCTGCTGCTTTC 88 GGGTGCAAGTG 5244 5244 5244 5244 TGTGAGATTTT GAGGAGATCTA 3443 3466 3593 3615 BAP1 chr3 89 CCCTGACATTTG 90 TCGGTAAGAGC 5244 5244 5244 5244 CTCTGAAGGT CTTTTCTCCCT 3570 3592 3710 3732 BAP1 chr3 91 TCTTACCGAAAT 92 AAGATGAATAA 5244 5244 5244 5244 CTTCCACGAGC GGGCTGGCTGG 3724 3747 3875 3897 BAP1 chrX 93 CTTACTGAACA 94 GTGGGAACAGA 7994 7994 7994 7994 CTGTAACACTG GCTAATATTCTC 8434 8462 8580 8608 GAAAGA AAGAG

TABLE 16 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop BRWD3 chrX 95 AGAGGATCCTC 96 CTAGAGGAGCT 7993 7993 7993 7993 AGTGGACACAA ACCAGAGCCAA 2193 2215 2343 2367 AC BRWD3 chrX 97 ATTGTTTTTACA 98 TTGATGTTAGGC 7999 7999 7999 7999 TGCCATTGCCAG TGAACATGAAA 1496 1522 1615 1645 AA ACTTTTT COL4A5 chrX 99 ATTAAATTCTCT 100 TGGGAAACCAC 1078 1078 1078 1078 GTGGCAAACAA GATCACCTTTT 4989 4992 5004 5006 TAAGGAC 3 3 5 7 COL4A5 chrX 101 CAGCTGGACAG 102 GTGTGTGGTAG 1079 1079 1079 1079 AAGGGTGAA CTTAGTAAGAA 0980 0982 0991 0993 AGAAGAT 1 1 0 9 COL4A5 chrX 103 CAAAAACTGGT 104 TGGAGGACCAG 1079 1079 1079 1079 TTCTCTCACACC CATCTCCTTTA 2488 2490 2503 2505 AAT 0 6 2 4 COL4A5 chrX 105 CCTCATTCTTTT 106 TCTCTCAGACTC 1079 1079 1079 1079 CCTGTAGGTCCA AAAGACTTTCC 2924 2926 2938 2941 A CT 2 7 8 3 COL4A5 chrX 107 CCTTGAAAGGC 108 TCTTGAAGCAA 1079 1079 1079 1079 TGTTTGCTATTG AGTTGCAAACA 3588 3591 3603 3606 T TTATTGA 9 3 4 3 COL4A5 chrX 109 CTGCTTGGAAG 110 CCCTAGCATCTC 1079 1079 1079 1079 AGTTTCGTTCAG TGAAGGAAGCT 3855 3857 3870 3872 0 3 1 4 CPEB1 chr15 111 CCCACCTGATCT 112 TGGCCAATAATG 8321 8321 8321 8321 CGACAGAAGA TGCCCTTCTT 5186 5208 5335 5357 CPEB1 chr15 113 CACAAGAAAAT 114 AAGTCTGTCCG 8322 8322 8322 8322 CCAGTGCCTCA ATCCTTGCTTC 1163 1186 1315 1337 A CPEB1 chr15 115 CTAACTGAGGG 116 GCTGTTGGCTG 8322 8322 8322 8322 TGCTGGAAACT CAAAGAAAACT 6619 6641 6770 6793 A ERBB2 chr17 117 GTTTGAGTGAA 118  GATCTCTTCCAG 3787 3787 3787 3787 GGCATTCATGGT AGTCTCAAACA 1434 1457 1582 1608 CTT ERBB2 chr17 119 CAAGAGGGTGG 120 GAGTGAAGGGC 3787 3787 3787 3787 TTCCCAGAATT AATGAAGGGTA 5993 6015 6108 6130 ERBB2 chr17 121 GGCTGGCTCCG 122 CAACGTAGCCA 3788 3788 3788 3788 ATGTATTTGAT TCAGTCTCAGA 3628 3650 3751 3773

TABLE 17 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_  Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop HSP90AA1 chr14 123 ATTACATAGTAT 124 CGACAAGTCTG 1025 1025 1025 1025 AAGGCTTACCC TGAAGGATCTG 4842 4845 4854 4857 AGACCA G 7 6 9 2 HSP90AA1 chr14 125 CCTGATAACTTT 126 GTCCTTGGAATG 1025 1025 1025 1025 CAAAATTTTGCT ACTCAGTGCAT 5022 5026 5034 5036 TTGTTGC 9 0 0 3 HSP90AA1 chr14 127 CAGACAGAAAT 128 CAGGTGAACCT 1025 1025 1025 1025 TCACTCTGCAAT ATGGGTCGT 5159 5162 5175 5177 TACATAAAA 7 9 1 1 HSP90AA1 chr14 129 CCCAAGAAGTT 130 TGAGACGTTCG 1025 1025 1025 1025 CACACTGAAAC CCTTTCAGG 5249 5252 5264 5266 C 9 2 5 5 IRAK1 chrX 131 CGCCTAGGCTCT 132 CCCGCAGGAGA 1532 1532 1532 1532 CGTCACT ACTCCTAC 7864 7866 7878 7880 4 3 2 1 IRAK1 chrX 133 CCAGGTGTCAG 134 ACAGGTTTCGT 1532 1532 1532 1532 GAGTGCTTT CACCCAAACA 8340 8342 8355 8357 1 1 4 5 KDM5C chrX 135 TCCGTACCCTCT 136 TGTCTTTCTGCC 5322 5322 5322 5322 TTGGCTCTAG TGTCTGTAATCA 2382 2404 2516 2541 C KDM5C chrX 137 CCAGAAGTGTG 138  AGTTGACTGGC 5322 5322 5322 5322 CGGATCCTC CCTGTGTTG 2621 2641 2768 2788 KDM5C chrX 139 CCCACACACAC 140 CTGTCCTGGGTA 5322 5322 5322 5322 AGATAGAGGTT TGGCAGATC 3786 3809 3917 3938 G KDM5C chrX 141 CCATCTGTGTCG 142 GTTCTCTGCCCA 5322 5322 5322 5322 AAGCTCCTT TGTGCAGAT 4090 4111 4229 4250 KDM5C chrX 143 CTCTTCTGGGTC 144  CCTAGCCCTGCT 5322 5322 5322 5322 TCCACTCAAC GTGGATAAAG 5798 5820 5943 5965 KDM5C chrX 145 CAGGTTGTTCAT 146 AGTCTTAGCATA 5322 5322 5322 5322 CTGGTCCAGAA GACATGGAGGG 6986 7009 7102 7127 AA KDM5C chrX 147 GCCTCACTCAG 148 CCTCTGCCTCTA 5322 5322 5322 5322 GCAGTTCTTTA TTCAATACTGCC 7723 7745 7847 7873 TA KDM5C chrX 149 CTACTGGAGCA 150 GATGATGAGCG 5322 5322 5322 5322 CTTGCAGAGAT CCAGTGTATCA 8174 8196 8276 8298

TABLE 18 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop KDM5C chrX 151 CCCGAACTTCC 152 CCAGAGAAGCT 5323 5323 5323 5323 ACCAGAATAGG AGACCTGAACC 0683 0705 0807 0830 T KDM5C chrX 153 CCATCTTGCAGA 154 GAAGCAGGAGG 5323 5323 5323 5323 TAAGCTCCTCA GTTGTAGAGAA 0839 0862 0981 1004 G KDM5C chrX 155 GCAAAGTTGTA 156 CAGGAAAATCT 5323 5323 5323 5323 GCCTTGGTTGA CTATCTCAACAG 1067 1089 1174 1201 CCAT KDM5C chrX 157 GAGGTCAGGCT 158 CCTGCATGACC 5323 5323 5323 5323 GGCTATCAAAT AAGGTGTGATT 9653 9675 9789 9811 KDM5C chrX 159 GGAGCCCACAC 160 GTACTGTGCCA 5323 5323 5323 5323 TGACTTGATTC CATCAATGCAG 9811 9833 9963 9985 KDM5C chrX 161 ATGCCAGAGATA 162 GTTCCCTAGGCT 5323 5323 5324 5324 TCTGCATTGATG AAAGAAAATGA 9951 9976 0094 0124 T CTTAAGA KDM5C chrX 163 AGATACTAAATG 164 TAGCATTGAGG 5324 5324 5324 5324 ATTTGCCTAAGC AAGATGTGACT 0617 0646 0764 0790 TCACA GTTG KDM5C chrX 165 GGGAATGCTTAT 166 CCTAAGACCTT 5324 5324 5324 5324 TGAAGGGACAA CCTGGAGAGCA 4917 4942 5055 5078 GA A KDM5C chrX 167 GTAGCCTCATGG 168 CCATTTTTCTCT 5324 5324 5324 5324 TCATCTTGGT CTCCCAGATAA 5003 5025 5151 5177 GGA KDM5C chrX 169 TCCCTCCACCTC 170 TAATGAGGAGA 5324 5324 5324 5324 AAAGCTCTAA AGGACAAGGAA 6280 6302 6406 6436 TACAAACC KDM5C chrX 171 GCAAGGAGCCA 172 CTACAGGCCTA 5324 5324 5324 5324 ATATTTTTGCCT CTCCCTCACATA 7043 7066 7194 7217 KDM5C chrX 173 ACCACCAGCTC 174 CTTTTGGTGACT 5324 5325 5325 5325 CTAGTCTTCTC TCCGGTCTTACA 9997 0019 0144 0168 KDM5C chrX 175 CGATGGGCCTGA 176 GCGCCATGAGT 5325 5325 5325 5325 TTTTCGC CCTTAAGG 3960 3979 4115 4134 KDM6A chrX 177 CCAAGCAAGAA 178 AGACTCATAGT 4487 4487 4487 4487 TTCATGCACGT CTGTGTTCACTT 9794 9816 9938 9966 TGAAC KDM6A chrX 179 CACTGTTCATTG 180 AAAAAGGAACA 4494 4494 4494 4494 GGTTCAGGCTA GTCCTATTGGAT 9108 9131 9215 9245 ATAATCC

TABLE 19 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_  ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop LRP12 chr8 181 ACCTCGGGTACT 182 AAGTTTGTTTTC 1055 1055 1055 1055 CTGAGTTGAG CGTGGAGTCTG 0337 0339 0352 0354 A 5 7 2 6 LRP12 chr8 183 TCCACGGAAAA 184 TTCCTATGGCAG 1055 1055 1055 1055 CAAACTTCTGTG GCAGATCAAG 0352 0355 0368 0370 A 9 3 1 3 NCOA6 chr20 185 CTGGGAAGTTT 186 CAAGGAGAGCT 3332 3332 3332 3332 GTTAGGATCCGA TGAATGTGCCT 9645 9669 9793 9815 A NCOA6 chr20 187 CCCAAAATGGC 188 GGCCATGGGAT 3333 3333 3333 3333 CTGCAGATATG GTCTTTCAATG 7295 7317 7434 7456 NCOA6 chr20  189 CTCCACTGAAA 190 GGTGATCCTGCT 3333 3333 3333 3333 GGTGCATTGAA ACTACAGCAAAT 7420 7443 7568 7594 A AA NCOA6 chr20 191 GCAGGGCTCAA 192 TTGGCTCAGAA 3335 3335 3335 3335 ATGATCAAATAA CCGAAGCCAAG 6193 6218 6343 6366 GC A NHS chrX 193  TCCAAGTAAATG 194 GGGATACCCGA 1774 1774 1774 1774 AAAATTTGTTTG GATGGTTTTCC 2356 2386 2505 2527 CCATTT NHS chrX 195 ACAGCAACCCT 196 TCTCCTACTGTG 1774 1774 1774 1774 CTTTAAAAGATG TTCTGCTTATTAT 5415 5441 5558 5588 GAA GAGTA NHS chrX 197 ACCGTCATCCAC 198 CTTAACTTCTTC 1774 1774 1774 1774 TGCATGTTTT AGACTTGTTGAT 5537 5559 5657 5685 GGAC RGAG1 chrX  199 GAATGATGTCAT 200 AGTGTGCACAT 1096 1096 1096 1096 CCATGCCACAA GTCTCCAGAAG 9633 9635 9648 9650 1 4 3 5 RGAG1 chrX 201 GTCCACATTGCA 202 CATGGGCATCGA 1096 1096 1096 1096 AACCAGTGTT TCCAGAAACT 9680 9683 9694 9697 9 1 9 1 RGAG1 chrX 203 CCACATCATTTA 204 TGTGGTGTGGA 1096 1096 1096 1096 TGAGAGCCTCA CATTGTTCCAG 9692 9695 9708 9710 GTT 8 4 0 2

TABLE 20 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop  Stop SCAF1 chr19 205 CCATGTGTCCCA 206 GGGTTCGTGAG 5014 5014 5014 5014 TTGGCTTCT CAAAGGAGG 5305 5326 5424 5444 SCAF1 chr19 207 CGCTTTAGCTCC 208 ACTAGCGACCC 5014 5014 5014 5014 GCCTCTC AACTCCGC 5405 5424 5555 5574 SCAF1 chr19 209 GGGACCTCCAC 210 CTCACCAGGAT 5014 5014 5014 5014 TCCAAACTCT AAAGGCAGAAG 8240 8261 8372 8396 GA SCAF1 chr19 211 ATGGTCCGCCA 212 GTGCTTCAAGG 5014 5014 5014 5014 GACAGAGA GAGCCAAGAGT 8342 8361 8484 8506 SCAF1 chr19 213 GCACTTGAGTCT 214 CCGCCATACCTT 5014 5014 5014 5014 AGCTGTCAGT TATCATTGGG 8503 8525 8655 8677 SH3TC1 chr4 215 CCACAGGCTTC 216 CAACGCTCACC 8217 8217 8217 8217 ACTCATCACTG TTCTTGGATGA 832 854 972 994 SH3TC1 chr4 217 CAGTGACCACC 218 GGCGGTGAAGA 8218 8218 8218 8218 TCCATCCTTTT GTCTGTTTCC 658 680 804 825 SH3TC1 chr4 219 TCTGTCTGTCAA 220 CCTGGCATCCTC 8224 8224 8224 8224 ATCAAGGAATG CTCAGAAAAG 473 500 623 645 GAAA TBC1D8 chrX 221 ATGAGATACATC 222 CATATCAGTCAT 1060 1060 1060 1060 AGCATGCTAATA GTGTTCTGTCA 9316 9319 9330 9333 GAAGTG GCT 0 0 8 4 TBC1D8B chrX 223 AGCAGACATGG 224 CAGTCAATCTG 1061 1061 1061 1061 TTTTTAAAATCT ATACTGTTCCAA 0894 0897 0909 0912 TCCAAA ATATGG 6 5 1 0 TBC1D8B chrX 225 CCATATTTGGAA 226 TACCAATTGCA 1061 1061 1061 1061 CAGTATCAGATT GAGGAGAATTC 0909 0912 0923 0926 GACTG TTTGAA 2 1 8 6 TBC1D8B chrX 227 TGGAAGGAAAC 228 CAACAGCGATG 1061 1061 1061 1061 TACATAGCCCTA CAAGAATCTGT 1691 1694 1707 1709 CA T 9 4 0 3 TET2 chr4 229 TAACTGCAGTG 230 AGTTCACCATG 1061 1061 1061 1061 GGCCTGAAAAT TGTGTGTTCCA 5560 5562 5575 5577 6 8 1 3 TET2 chr4 231 CCTGTGATGCTG 232 AATTCTTCACCA 1061 1061 1061 1061 ATGATGCTGATA GACGCTAGCTT 5598 5600 5613 5615 3 7 1 4 TET2 chr4 233 GGAAAAAGCAC 234 GCCTTTCAGAA 1061 1061 1061 1061 TCTGAATGGTG AGCATCGGAGA 5636 5638 5651 5653 GA A 3 7 4 7

TABLE 21 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_Primer* NO Rev_Primer* Start Start Stop Stop TET2 chr4 235 AACTGCCAGCA 236 TTACGTTTTAGA 1061 1061 1061 1061 GTTGATGAGAA TGGGATTCCGCT 5668 5670 5681 5684 T 1 3 9 4 TET2 chr4 237 CACCAAGCGGA 238 AGCTGTGTTGTT 1061 1061 1061 1061 ATCCCATCTAA TTCTGGGTGTA 5681 5683 5695 5697 6 8 6 9 TET2 chr4 239 AAACACAACCA 240 CCATGAAAACA 1061 1061 1061 1061 TCCCAGAGTTC TTCTTCCACTTT 5728 5730 5743 5745 A AGTCTG 5 8 0 9 TET2 chr4 241 GGGTCACTGCAT 242 GCAGTGTGAGA 1061 1061 1061 1061 GTTTGGACTT ACAGACTCAAC 9083 9085 9093 9095 AG 1 3 2 6 TET2 chr4 243 AAGTCTCTGAC 244 GAAAGCTTTTC 1061 1061 1061 1061 GTGGATGAGTTT AGCTGCAGCTT 9380 9382 9395 9397 G 3 7 5 7 TET2 chr4 245 AGGTTTGGAAAT 246 ATCTAGAGGTG 1061 1061 1061 1061 AGCCAGAGTTTT GCTCCCATGAA 9671 9673 9686 9688 ACA 1 8 3 5 TEX13A chrX 247 TCGAGATATACA 248 CTCATCAGCAA 1044 1044 1044 1044 TGCTTCGGTTCT AGACCTCCAGT 6360 6363 6375 6377 ATTTTG A 5 5 6 9 TEX13A chrX 249 GGGTTCGTGGTT 250 CCTCCATGGAG 1044 1044 1044 1044 CCAGAGAAAT ACCACAGAGAA 6402 6405 6415 6417 8 0 6 8 TEX13A chrX 251 TCTCTCCAGCTT 252 CTGCTGGAGGA 1044 1044 1044 1044 CTCTGTGGT AAAGGAGCAGA 6414 6416 6429 6431 7 8 6 8 ULK3 chr15 253 GCCTGAAGAGA 254 CCAAGAAAAGT 7513 7513 7513 7513 GTGTCCCTTCT CTGAACAAGGC 4560 4582 4700 4724 AT WNK3 chrX 255 GCTGAAGAGAA 256 CCTGGCTTCTTC 5427 5427 5427 5427 GGAGGAGACTG AGTCAATAAGG 6466 6489 6610 6640 A TAAATAA WNK3 chrX 257 GAAACTTGCTG 258 GGCAGGAGCTG 5431 5431 5431 5431 GTAATGTCCTAC CATCAGTTATA 9571 9598 9722 9744 TAGT WNK3 chrX 259 GTGCTGCTGTG 260 GGGATTCTCAG 5432 5432 5432 5432 GTTTTCTTTGTA TGCAAGTCTATG 1002 1025 1135 1159 G

TABLE 22 SEQ SEQ Lineitem_ ID Ion_AmpliSeq_ ID Ion_AmpliSeq_ Amplicon_ Insert_ Insert_ Amplicon_ Name Chr NO Fwd_ Primer* NO Rev_Primer* Start Stop Start Stop ARSF chrX 261 GTGCATGACGA 262 ACGACTGACGA 2990 2990 2990 2990 CAAGCCTAATAT ACGTATGACTG 128 153 234 256 TG CFPX chrX 263 GCTGTAGCAGT 264 ACATGAAGTCC 4748 4748 4748 4748 GCCGGATAT ATCAGCTGTCA 5743 5763 5843 5867 AG CFP chrX 265 CCGGGATTTCTT 266 TGATTCCCTGCT 4748 4748 4748 4748 GACAGCTGAT TTGGTCCAATC 5835 5857 5940 5963 CFP chrX 267 CCCACTCTGAG 268 GAATGGGCAGT 4748 4748 4748 4748 GACCTCTGTA GCTCTGGAA 7417 7438 7563 7583 CFP chrX 269 GGCAAAGGCAG 270 GTGTCCAGGCC 4748 4748 4748 4748 TGTTGAGAC CACCACAT 8961 8981 9116 9135 FAM47A chrX 271 ACTGGATCTCCG 272 GAGACTGGAGT 3414 3414 3414 3414 ACGAGTGAT GTCCCATCTAAG 9619 9640 9760 9783 JADE3 chrX 273 ACGCCATTGCCA 274 TCCACTCTCACT 4688 4688 4688 4688 TGAAAATATGAA AACCTGATGCA 7346 7371 7497 7520 C JADE3 chrX 275 CCATTCTAGGAG 276 GCCATTGGATTT 4691 4691 4691 4691 TGAAGCAAAGG GGCAAACTTG 7837 7861 7989 8011 A ZNF449 chrX 277 GGAGCTGAACT 278 CATTGAGTAATT 1344 1344 1344 1344 ATGGTGCTACT GGTGTTTCTAAC 8319 8321 8330 8333 CCAAC 0 2 7 6 SCRN1 chr7 279 TTTTGCTGGTAA 280 CCTGGAAGCCA 2996 2996 2996 2996 TTTAGTAAGGTG TGGAAGAAATC 3511 3539 3658 3681 GGAA C SCRN1 chr7 281 AGGGTATGAGA 282 GAACTCAGGAG 2998 2998 2998 2998 AGGAGAATCGT TTACGCTCAGA 0257 0281 0408 0430 GA

To verify whether the mutations of the genes were detected using the constructed primer sets, the gene mutations verified in Example 2 and a DNA test samples derived from wild-type kidney cancer cells were amplified. Specifically, each of the gene mutations and the DNA test samples used as the test sample was amplified using a primer set corresponding to each of the test samples, respectively. Thereafter, the amplified chips were scanned using a scanner and application program, and analyzed using quantitative analysis software.

As a result, it can be seen that the mutations of the genes of Examples 2 and 3 were detected using the primer sets constructed in Example 4. On the other hand, the mutations were not detected in the test samples derived from the kidney cancer cells as the control. As described above, because the mutations of genes selected from a gene group consisting of ACSS3, ADAM21, AFF2, ALG13, BAP1, BRWD3, COL4A5, CPEB1, ERBB2, HSP90AA1, IRAK1, KDMSC, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TBC1D8B, TET2, TEX13A, ULK3, WNK3, ARSF, CFP, FAM47A, PHF16, ZNF449, and SCRN1 were detectable using the primer sets listed in Tables 14 to 22, it was possible to predict the overall survival Kaplan-Meier estimates and disease-free survival Kaplan-Meier estimates of the patients with kidney cancer in which the genes were mutated, thereby effectively designing a therapeutic strategy for kidney cancer.

Although preferred embodiments of the present invention have been shown and described for the purpose of illustration only, it would be appreciated by those skilled in the art that various modifications and changes may be made in these embodiments without departing from the scope of the present invention. 

1-12. (canceled)
 13. A method of providing information required to verify a difference in therapeutic effect against kidney cancer according to the gender of a patient with kidney cancer, the method comprising: preparing a DNA test sample from a sample of a patient with kidney cancer whose gender is identified; identifying the presence or absence of a gender specific marker in a DNA test sample; treating the patient with kidney cancer, in which the gender-specific marker is identified, with any candidate material for treating kidney cancer or healing the patient with kidney cancer using any method; and choosing any candidate material for treating kidney cancer or any method of treating kidney cancer as a therapeutic candidate material or a therapeutic method, which is suitable for the gender group of patients with kidney cancer in which the gender-specific marker is identified, when the any candidate material or the any method is used to treat kidney cancer, wherein the gender specific marker is a mutation of a gene coding for ADAM21, wherein the mutation of a gene coding for ADAM21 is at least one mutation selected from the group consisting of N265Y, R408C, T589S, and I161V in the amino acid sequence set forth in SEQ ID NO:
 2. 14. The method of claim 13, wherein the patient with kidney cancer is a female.
 15. The method of claim 13, wherein the gender-specific marker further comprises a mutation of a gene coding for one selected from the group consisting of ALG13, BRWD3, CPEB1, ERBB2, HSP90AA1, IRAK1, KDM6A, LRP12, NCOA6, NHS, RGAG1, SCAF1, SH3TC1, TEX13A, ULK3, WNK3, ARSF, CFP, PHF16, ZNF449, and SCRN1.
 16. The method of claim 15, wherein the mutation of the gene coding for ALG13 is at least one missense mutation selected from P925T and V456E, or a frameshift deletion (FS del) mutation ‘L195Pfs*23’ in the amino acid sequence set forth in SEQ ID NO: 4; the mutation of the gene coding for BRWD3 is at least one missense mutation selected from G287A and I1747N in the amino acid sequence set forth in SEQ ID NO: 6; the mutation of the gene coding for CPEB1 is at least one missense mutation selected from S393R and G136V, or a splice mutation ‘X499_splice’ (where C is substituted with A at position 83215272 on the chromosome) in the amino acid sequence set forth in SEQ ID NO: 8; the mutation of the gene coding for ERBB2 is at least one missense mutation selected from the group consisting of E1114G, 5649T, and V219I, or a frameshift insertion (FS ins) mutation ‘N388Qfs*14’ in the amino acid sequence set forth in SEQ ID NO: 9; the mutation of the gene coding for HSP90AA1 is at least one missense mutation selected from the group consisting of D512N, H806R, I325T, and L167V in the amino acid sequence set forth in SEQ ID NO: 10; the mutation of the gene coding for IRAK1 is a nonsense mutation ‘Q280*’, or at least one missense mutation selected from V548M and Q584K in the amino acid sequence set forth in SEQ ID NO: 11; the mutation of the gene coding for KDM6A is a missense mutation ‘A3OV’, an FS mutation ‘A1246Pfs*19’, or an IF del mutation ‘V156del’ in the amino acid sequence set forth in SEQ ID NO: 13; the mutation of the gene coding for LRP12 is at least one missense mutation selected from the group consisting of S622L, E639K, and V671I in the amino acid sequence set forth in SEQ ID NO: 14; the mutation of the gene coding for NCOA6 is at least one missense mutation selected from the group consisting of G164E, N877I, N864Y, and V1444A, or an FS ins mutation ‘H832Sfs*47’ in the amino acid sequence set forth in SEQ ID NO: 15; the mutation of the gene coding for NHS is at least one missense mutation selected from the group consisting of C360R, P1107A, and D1069H in the amino acid sequence set forth in SEQ ID NO: 16; the mutation of the gene coding for RGAG1 is at least one missense mutation selected from the group consisting of A1015G, M858V, and G1053R in the amino acid sequence set forth in SEQ ID NO: 17; the mutation of the gene coding for SCAF1 is at least one FS ins mutation selected from the group consisting of A219Sfs*11, P211Tfs*19, P211Tfs*19, and A216Pfs*94, or an FS del mutation ‘A216Pfs*94’ in the amino acid sequence set forth in SEQ ID NO: 18; the mutation of the gene coding for SH3TC1 is at least one missense mutation selected from A375V and L180F or an FS del mutation ‘R238Sfs*38’ in the amino acid sequence set forth in SEQ ID NO: 19; the mutation of the gene coding for TEX13A is at leasint one missense mutation selected from R393S and Y257D, or a splice mutation ‘X199_splice’ (where C at position 104464282 is deleted from the chromosome) in the amino acid sequence set forth in SEQ ID NO: 22; the mutation of the gene coding for ULK3 is an FS del mutation ‘Q81Sfs*41’ and at least one missense mutation selected from D79H and L77V in the amino acid sequence set forth in SEQ ID NO: 23; the mutation of the gene coding for WNK3 is at least one nonsense mutation selected from S865* and Y589* and a missense mutation ‘E537G’ in the amino acid sequence set forth in SEQ ID NO: 24; the mutation of the gene coding for ARSF is a missense mutation ‘I42F’ in the amino acid sequence set forth in SEQ ID NO: 25; the mutation of the gene coding for CFP is at least one missense mutation selected from the group consisting of S27L, R359Q, and E135K, or an FS ins mutation ‘E323Gfs*34’ in the amino acid sequence set forth in SEQ ID NO: 26; the mutation of the gene coding for PHF16 is at least one missense mutation selected from K656Q and R207W in the amino acid sequence set forth in SEQ ID NO: 28; the mutation of the gene coding for ZNF449 is a missense mutation ‘F1831’ in the amino acid sequence set forth in SEQ ID NO: 29; and the mutation of the gene coding for SCRN1 is a missense mutation ‘D427Y’ or an FS ins mutation ‘A257Cfs*34’ in the amino acid sequence set forth in SEQ ID NO:
 30. 17. A method of providing information required to diagnose prognosis of kidney cancer according to the gender of a patient with kidney cancer, the method comprising: preparing a DNA test sample from a sample of a patient with kidney cancer; identifying the presence or absence of a gender specific maker in a DNA test sample; and judging that the survival rate of the patient with kidney cancer is not good or the relapse rate of kidney cancer in the patient with kidney cancer is high when the gender-specific marker is identified; wherein the gender specific marker is a mutation of a gene coding for ADAM21, wherein the mutation of a gene coding for ADAM21 is at least one mutation selected from the group consisting of N265Y, R408C, T589S, and I161V in the amino acid sequence set forth in SEQ ID NO:
 2. 18. The method of claim 17, wherein the gender-specific marker further comprises a mutation of a gene coding for one selected from the group consisting of ALG13, ARSF, KDM6A, PHF16, ZNF449, and SCRN1; wherein the mutation of the gene coding for ALG13 is at least one missense mutation selected from P925T and V456E, or a frameshift deletion (FS del) mutation ‘L195Pfs*23’ in the amino acid sequence set forth in SEQ ID NO: 4; the mutation of the gene coding for ARSF is a missense mutation ‘I42F’ in the amino acid sequence set forth in SEQ ID NO: 25; the mutation of the gene coding for KDM6A is a missense mutation ‘A30V’, an FS mutation ‘A1246Pfs*19’, or an IF del mutation ‘V156del’ in the amino acid sequence set forth in SEQ ID NO: 13; the mutation of the gene coding for PHF16 is at least one missense mutation selected from K656Q and R207W in the amino acid sequence set forth in SEQ ID NO: 28; the mutation of the gene coding for ZNF449 is a missense mutation ‘F1831’ in the amino acid sequence set forth in SEQ ID NO: 29; and the mutation of the gene coding for SCRN1 is a missense mutation ‘D427Y’ or an FS ins mutation ‘A257Cfs*34’ in the amino acid sequence set forth in SEQ ID NO:
 30. 